Package evaluation to test Baytes on Julia 1.14.0-DEV.1352 (749bc618c5*) started at 2025-12-09T23:28:50.760 ################################################################################ # Set-up # Installing PkgEval dependencies (TestEnv)... Activating project at `~/.julia/environments/v1.14` Set-up completed after 9.7s ################################################################################ # Installation # Installing Baytes... Resolving package versions... Updating `~/.julia/environments/v1.14/Project.toml` [72ddfcfc] + Baytes v0.3.16 Updating `~/.julia/environments/v1.14/Manifest.toml` [621f4979] + AbstractFFTs v1.5.0 [7d9f7c33] + Accessors v0.1.43 [79e6a3ab] + Adapt v4.4.0 [66dad0bd] + AliasTables v1.1.3 [dce04be8] + ArgCheck v2.5.0 [72ddfcfc] + Baytes v0.3.16 [e5a8efeb] + BaytesCore v0.2.0 [12a76ff9] + BaytesDiff v0.3.1 [26b78818] + BaytesFilters v0.3.6 [8e6e46a0] + BaytesMCMC v0.3.4 [c78c806d] + BaytesOptim v0.1.9 [c4a8eb41] + BaytesPMCMC v0.3.3 [2428e3a5] + BaytesSMC v0.3.6 ⌅ [76274a88] + Bijectors v0.13.18 [082447d4] + ChainRules v1.72.6 [d360d2e6] + ChainRulesCore v1.26.0 [9e997f8a] + ChangesOfVariables v0.1.10 [38540f10] + CommonSolve v0.2.4 [34da2185] + Compat v4.18.1 [a33af91c] + CompositionsBase v0.1.2 [187b0558] + ConstructionBase v1.6.0 [a8cc5b0e] + Crayons v4.1.1 [9a962f9c] + DataAPI v1.16.0 [864edb3b] + DataStructures v0.19.3 [e2d170a0] + DataValueInterfaces v1.0.0 [31c24e10] + Distributions v0.25.122 [ffbed154] + DocStringExtensions v0.9.5 [fdbdab4c] + ElasticArrays v1.2.12 [5789e2e9] + FileIO v1.17.1 [1a297f60] + FillArrays v1.15.0 ⌅ [d9f16b24] + Functors v0.4.12 [46192b85] + GPUArraysCore v0.2.0 [34004b35] + HypergeometricFunctions v0.3.28 [3587e190] + InverseFunctions v0.1.17 [92d709cd] + IrrationalConstants v0.2.6 [82899510] + IteratorInterfaceExtensions v1.0.0 ⌅ [033835bb] + JLD2 v0.4.55 [692b3bcd] + JLLWrappers v1.7.1 [b964fa9f] + LaTeXStrings v1.4.0 [2ab3a3ac] + LogExpFunctions v0.3.29 [be115224] + MCMCDiagnosticTools v0.3.15 [e80e1ace] + MLJModelInterface v1.12.1 [1914dd2f] + MacroTools v0.5.16 [dbb5928d] + MappedArrays v0.4.2 [e1d29d7a] + Missings v1.2.0 [44c54197] + ModelWrappers v0.5.6 [bac558e1] + OrderedCollections v1.8.1 [90014a1f] + PDMats v0.11.36 [aea7be01] + PrecompileTools v1.3.3 [21216c6a] + Preferences v1.5.0 ⌅ [08abe8d2] + PrettyTables v2.4.0 [92933f4c] + ProgressMeter v1.11.0 [43287f4e] + PtrArrays v1.3.0 [1fd47b50] + QuadGK v2.11.2 [c1ae055f] + RealDot v0.1.0 [189a3867] + Reexport v1.2.2 [ae029012] + Requires v1.3.1 [79098fc4] + Rmath v0.9.0 [f2b01f46] + Roots v2.2.10 [30f210dd] + ScientificTypesBase v3.0.0 [ce78b400] + SimpleUnPack v1.1.0 [a2af1166] + SortingAlgorithms v1.2.2 [dc90abb0] + SparseInverseSubset v0.1.2 [276daf66] + SpecialFunctions v2.6.1 [64bff920] + StatisticalTraits v3.5.0 [10745b16] + Statistics v1.11.1 [82ae8749] + StatsAPI v1.8.0 [2913bbd2] + StatsBase v0.34.9 [4c63d2b9] + StatsFuns v1.5.2 [892a3eda] + StringManipulation v0.4.2 [09ab397b] + StructArrays v0.7.2 [3783bdb8] + TableTraits v1.0.1 [bd369af6] + Tables v1.12.1 [3bb67fe8] + TranscodingStreams v0.11.3 [efe28fd5] + OpenSpecFun_jll v0.5.6+0 [f50d1b31] + Rmath_jll v0.5.1+0 [0dad84c5] + ArgTools v1.1.2 [56f22d72] + Artifacts v1.11.0 [2a0f44e3] + Base64 v1.11.0 [ade2ca70] + Dates v1.11.0 [8ba89e20] + Distributed v1.11.0 [f43a241f] + Downloads v1.7.0 [7b1f6079] + FileWatching v1.11.0 [b77e0a4c] + InteractiveUtils v1.11.0 [ac6e5ff7] + JuliaSyntaxHighlighting v1.13.0 [b27032c2] + LibCURL v1.0.0 [76f85450] + LibGit2 v1.11.0 [8f399da3] + Libdl v1.11.0 [37e2e46d] + LinearAlgebra v1.13.0 [56ddb016] + Logging v1.11.0 [d6f4376e] + Markdown v1.11.0 [a63ad114] + Mmap v1.11.0 [ca575930] + NetworkOptions v1.3.0 [44cfe95a] + Pkg v1.14.0 [de0858da] + Printf v1.11.0 [3fa0cd96] + REPL v1.11.0 [9a3f8284] + Random v1.11.0 [ea8e919c] + SHA v1.0.0 [9e88b42a] + Serialization v1.11.0 [6462fe0b] + Sockets v1.11.0 [2f01184e] + SparseArrays v1.13.0 [f489334b] + StyledStrings v1.13.0 [4607b0f0] + SuiteSparse [fa267f1f] + TOML v1.0.3 [a4e569a6] + Tar v1.10.0 [cf7118a7] + UUIDs v1.11.0 [4ec0a83e] + Unicode v1.11.0 [e66e0078] + CompilerSupportLibraries_jll v1.3.0+1 [deac9b47] + LibCURL_jll v8.17.0+0 [e37daf67] + LibGit2_jll v1.9.1+0 [29816b5a] + LibSSH2_jll v1.11.3+1 [14a3606d] + MozillaCACerts_jll v2025.12.2 [4536629a] + OpenBLAS_jll v0.3.29+0 [05823500] + OpenLibm_jll v0.8.7+0 [458c3c95] + OpenSSL_jll v3.5.4+0 [efcefdf7] + PCRE2_jll v10.47.0+0 [bea87d4a] + SuiteSparse_jll v7.10.1+0 [83775a58] + Zlib_jll v1.3.1+2 [3161d3a3] + Zstd_jll v1.5.7+1 [8e850b90] + libblastrampoline_jll v5.15.0+0 [8e850ede] + nghttp2_jll v1.68.0+1 [3f19e933] + p7zip_jll v17.7.0+0 Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading. To see why use `status --outdated -m` Installation completed after 4.9s ################################################################################ # Precompilation # ERROR: LoadError: MethodError: no method matching setindex!(::Base.ScopedValues.ScopedValue{IO}, ::Nothing) The function `setindex!` exists, but no method is defined for this combination of argument types. Stacktrace: [1] top-level scope @ /PkgEval.jl/scripts/precompile.jl:10 [2] include(mod::Module, _path::String) @ Base ./Base.jl:309 [3] exec_options(opts::Base.JLOptions) @ Base ./client.jl:344 [4] _start() @ Base ./client.jl:577 in expression starting at /PkgEval.jl/scripts/precompile.jl:6 caused by: MethodError: no method matching setindex!(::Base.ScopedValues.ScopedValue{IO}, ::Base.DevNull) The function `setindex!` exists, but no method is defined for this combination of argument types. Stacktrace: [1] top-level scope @ /PkgEval.jl/scripts/precompile.jl:7 [2] include(mod::Module, _path::String) @ Base ./Base.jl:309 [3] exec_options(opts::Base.JLOptions) @ Base ./client.jl:344 [4] _start() @ Base ./client.jl:577 Precompilation failed after 13.22s ################################################################################ # Testing # Testing Baytes Status `/tmp/jl_2is9JV/Project.toml` [dce04be8] ArgCheck v2.5.0 [72ddfcfc] Baytes v0.3.16 [e5a8efeb] BaytesCore v0.2.0 [12a76ff9] BaytesDiff v0.3.1 [26b78818] BaytesFilters v0.3.6 [8e6e46a0] BaytesMCMC v0.3.4 [c78c806d] BaytesOptim v0.1.9 [c4a8eb41] BaytesPMCMC v0.3.3 [2428e3a5] BaytesSMC v0.3.6 [31c24e10] Distributions v0.25.122 [ffbed154] DocStringExtensions v0.9.5 ⌃ [f6369f11] ForwardDiff v0.10.39 ⌅ [033835bb] JLD2 v0.4.55 [be115224] MCMCDiagnosticTools v0.3.15 [44c54197] ModelWrappers v0.5.6 [d41bc354] NLSolversBase v7.10.0 [429524aa] Optim v1.13.3 ⌅ [08abe8d2] PrettyTables v2.4.0 [92933f4c] ProgressMeter v1.11.0 [ce78b400] SimpleUnPack v1.1.0 [10745b16] Statistics v1.11.1 [ade2ca70] Dates v1.11.0 [9a3f8284] Random v1.11.0 [8dfed614] Test v1.11.0 Status `/tmp/jl_2is9JV/Manifest.toml` [47edcb42] ADTypes v1.20.0 [621f4979] AbstractFFTs v1.5.0 [7d9f7c33] Accessors v0.1.43 [79e6a3ab] Adapt v4.4.0 [66dad0bd] AliasTables v1.1.3 [dce04be8] ArgCheck v2.5.0 [4fba245c] ArrayInterface v7.22.0 [72ddfcfc] Baytes v0.3.16 [e5a8efeb] BaytesCore v0.2.0 [12a76ff9] BaytesDiff v0.3.1 [26b78818] BaytesFilters v0.3.6 [8e6e46a0] BaytesMCMC v0.3.4 [c78c806d] BaytesOptim v0.1.9 [c4a8eb41] BaytesPMCMC v0.3.3 [2428e3a5] BaytesSMC v0.3.6 ⌅ [76274a88] Bijectors v0.13.18 [082447d4] ChainRules v1.72.6 [d360d2e6] ChainRulesCore v1.26.0 [9e997f8a] ChangesOfVariables v0.1.10 [38540f10] CommonSolve v0.2.4 [bbf7d656] CommonSubexpressions v0.3.1 [34da2185] Compat v4.18.1 [a33af91c] CompositionsBase v0.1.2 [187b0558] ConstructionBase v1.6.0 [a8cc5b0e] Crayons v4.1.1 [9a962f9c] DataAPI v1.16.0 [864edb3b] DataStructures v0.19.3 [e2d170a0] DataValueInterfaces v1.0.0 [163ba53b] DiffResults v1.1.0 [b552c78f] DiffRules v1.15.1 [a0c0ee7d] DifferentiationInterface v0.7.12 [31c24e10] Distributions v0.25.122 [ffbed154] DocStringExtensions v0.9.5 [fdbdab4c] ElasticArrays v1.2.12 [4e289a0a] EnumX v1.0.5 [5789e2e9] FileIO v1.17.1 [1a297f60] FillArrays v1.15.0 [6a86dc24] FiniteDiff v2.29.0 ⌃ [f6369f11] ForwardDiff v0.10.39 ⌅ [d9f16b24] Functors v0.4.12 [46192b85] GPUArraysCore v0.2.0 [34004b35] HypergeometricFunctions v0.3.28 [3587e190] InverseFunctions v0.1.17 [92d709cd] IrrationalConstants v0.2.6 [82899510] IteratorInterfaceExtensions v1.0.0 ⌅ [033835bb] JLD2 v0.4.55 [692b3bcd] JLLWrappers v1.7.1 [b964fa9f] LaTeXStrings v1.4.0 [d3d80556] LineSearches v7.5.1 [2ab3a3ac] LogExpFunctions v0.3.29 [be115224] MCMCDiagnosticTools v0.3.15 [e80e1ace] MLJModelInterface v1.12.1 [1914dd2f] MacroTools v0.5.16 [dbb5928d] MappedArrays v0.4.2 [e1d29d7a] Missings v1.2.0 [44c54197] ModelWrappers v0.5.6 [d41bc354] NLSolversBase v7.10.0 [77ba4419] NaNMath v1.1.3 [429524aa] Optim v1.13.3 [bac558e1] OrderedCollections v1.8.1 [90014a1f] PDMats v0.11.36 [85a6dd25] PositiveFactorizations v0.2.4 [aea7be01] PrecompileTools v1.3.3 [21216c6a] Preferences v1.5.0 ⌅ [08abe8d2] PrettyTables v2.4.0 [92933f4c] ProgressMeter v1.11.0 [43287f4e] PtrArrays v1.3.0 [1fd47b50] QuadGK v2.11.2 [c1ae055f] RealDot v0.1.0 [189a3867] Reexport v1.2.2 [ae029012] Requires v1.3.1 [79098fc4] Rmath v0.9.0 [f2b01f46] Roots v2.2.10 [30f210dd] ScientificTypesBase v3.0.0 [efcf1570] Setfield v1.1.2 [ce78b400] SimpleUnPack v1.1.0 [a2af1166] SortingAlgorithms v1.2.2 [dc90abb0] SparseInverseSubset v0.1.2 [276daf66] SpecialFunctions v2.6.1 [1e83bf80] StaticArraysCore v1.4.4 [64bff920] StatisticalTraits v3.5.0 [10745b16] Statistics v1.11.1 [82ae8749] StatsAPI v1.8.0 [2913bbd2] StatsBase v0.34.9 [4c63d2b9] StatsFuns v1.5.2 [892a3eda] StringManipulation v0.4.2 [09ab397b] StructArrays v0.7.2 [3783bdb8] TableTraits v1.0.1 [bd369af6] Tables v1.12.1 [3bb67fe8] TranscodingStreams v0.11.3 [efe28fd5] OpenSpecFun_jll v0.5.6+0 [f50d1b31] Rmath_jll v0.5.1+0 [0dad84c5] ArgTools v1.1.2 [56f22d72] Artifacts v1.11.0 [2a0f44e3] Base64 v1.11.0 [ade2ca70] Dates v1.11.0 [8ba89e20] Distributed v1.11.0 [f43a241f] Downloads v1.7.0 [7b1f6079] FileWatching v1.11.0 [9fa8497b] Future v1.11.0 [b77e0a4c] InteractiveUtils v1.11.0 [ac6e5ff7] JuliaSyntaxHighlighting v1.13.0 [b27032c2] LibCURL v1.0.0 [76f85450] LibGit2 v1.11.0 [8f399da3] Libdl v1.11.0 [37e2e46d] LinearAlgebra v1.13.0 [56ddb016] Logging v1.11.0 [d6f4376e] Markdown v1.11.0 [a63ad114] Mmap v1.11.0 [ca575930] NetworkOptions v1.3.0 [44cfe95a] Pkg v1.14.0 [de0858da] Printf v1.11.0 [3fa0cd96] REPL v1.11.0 [9a3f8284] Random v1.11.0 [ea8e919c] SHA v1.0.0 [9e88b42a] Serialization v1.11.0 [6462fe0b] Sockets v1.11.0 [2f01184e] SparseArrays v1.13.0 [f489334b] StyledStrings v1.13.0 [4607b0f0] SuiteSparse [fa267f1f] TOML v1.0.3 [a4e569a6] Tar v1.10.0 [8dfed614] Test v1.11.0 [cf7118a7] UUIDs v1.11.0 [4ec0a83e] Unicode v1.11.0 [e66e0078] CompilerSupportLibraries_jll v1.3.0+1 [deac9b47] LibCURL_jll v8.17.0+0 [e37daf67] LibGit2_jll v1.9.1+0 [29816b5a] LibSSH2_jll v1.11.3+1 [14a3606d] MozillaCACerts_jll v2025.12.2 [4536629a] OpenBLAS_jll v0.3.29+0 [05823500] OpenLibm_jll v0.8.7+0 [458c3c95] OpenSSL_jll v3.5.4+0 [efcefdf7] PCRE2_jll v10.47.0+0 [bea87d4a] SuiteSparse_jll v7.10.1+0 [83775a58] Zlib_jll v1.3.1+2 [3161d3a3] Zstd_jll v1.5.7+1 [8e850b90] libblastrampoline_jll v5.15.0+0 [8e850ede] nghttp2_jll v1.68.0+1 [3f19e933] p7zip_jll v17.7.0+0 Info Packages marked with ⌃ and ⌅ have new versions available. Those with ⌃ may be upgradable, but those with ⌅ are restricted by compatibility constraints from upgrading. Testing Running tests... ┌ Warning: The call to compilecache failed to create a usable precompiled cache file for Baytes [72ddfcfc-6e9d-43df-829b-7aed7c549d4f] │ exception = Required dependency Base.PkgId(Base.UUID("892a3eda-7b42-436c-8928-eab12a02cf0e"), "StringManipulation") failed to load from a cache file. └ @ Base loading.jl:2891 ┌ Warning: The call to compilecache failed to create a usable precompiled cache file for PrettyTables [08abe8d2-0d0c-5749-adfa-8a2ac140af0d] │ exception = Required dependency Base.PkgId(Base.UUID("892a3eda-7b42-436c-8928-eab12a02cf0e"), "StringManipulation") failed to load from a cache file. └ @ Base loading.jl:2891 Constructing new sampler... Sampling starts... Sampling starts... ┌───┬───────┬───────┬────────┬────────┬────────┬───────┬────────┬────────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼───────┼───────┼────────┼────────┼────────┼───────┼────────┼────────┼──────────┼──────────┼───────┤ │ μ │ 0.146 │ 0.253 │ 0.078 │ -0.286 │ -0.033 │ 0.156 │ 0.338 │ 0.631 │ 11.749 │ 10.01 │ 1.289 │ │ σ │ 9.992 │ 0.15 │ 0.025 │ 9.706 │ 9.88 │ 10.0 │ 10.078 │ 10.339 │ 27.676 │ 82.581 │ 1.131 │ └───┴───────┴───────┴────────┴────────┴────────┴───────┴────────┴────────┴──────────┴──────────┴───────┘ ┌───┬──────┬───────┬───────┬────────┬────────┬────────┬───────┬────────┬────────┬──────────┬──────────┬───────┐ │ │ True │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼──────┼───────┼───────┼────────┼────────┼────────┼───────┼────────┼────────┼──────────┼──────────┼───────┤ │ μ │ 0.0 │ 0.146 │ 0.253 │ 0.078 │ -0.286 │ -0.033 │ 0.156 │ 0.338 │ 0.631 │ 11.749 │ 10.01 │ 1.289 │ │ σ │ 10.0 │ 9.992 │ 0.15 │ 0.025 │ 9.706 │ 9.88 │ 10.0 │ 10.078 │ 10.339 │ 27.676 │ 82.581 │ 1.131 │ └───┴──────┴───────┴───────┴────────┴────────┴────────┴───────┴────────┴────────┴──────────┴──────────┴───────┘ Constructing new sampler... Sampling starts... Sampling starts... Constructing new sampler... Sampling starts... Sampling starts... Constructing new sampler... Sampling starts... Sampling starts... ┌───┬────────┬───────┬────────┬────────┬────────┬───────┬────────┬────────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼────────┼───────┼────────┼────────┼────────┼───────┼────────┼────────┼──────────┼──────────┼───────┤ │ μ │ 0.054 │ 0.259 │ 0.051 │ -0.182 │ -0.079 │ 0.0 │ 0.035 │ 0.775 │ 21.653 │ 12.644 │ 1.414 │ │ σ │ 10.019 │ 0.156 │ 0.016 │ 9.595 │ 9.959 │ 10.0 │ 10.101 │ 10.316 │ 61.514 │ 92.079 │ 1.298 │ └───┴────────┴───────┴────────┴────────┴────────┴───────┴────────┴────────┴──────────┴──────────┴───────┘ ┌───┬──────┬────────┬───────┬────────┬────────┬────────┬───────┬────────┬────────┬──────────┬──────────┬───────┐ │ │ True │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼──────┼────────┼───────┼────────┼────────┼────────┼───────┼────────┼────────┼──────────┼──────────┼───────┤ │ μ │ 0.0 │ 0.054 │ 0.259 │ 0.051 │ -0.182 │ -0.079 │ 0.0 │ 0.035 │ 0.775 │ 21.653 │ 12.644 │ 1.414 │ │ σ │ 10.0 │ 10.019 │ 0.156 │ 0.016 │ 9.595 │ 9.959 │ 10.0 │ 10.101 │ 10.316 │ 61.514 │ 92.079 │ 1.298 │ └───┴──────┴────────┴───────┴────────┴────────┴────────┴───────┴────────┴────────┴──────────┴──────────┴───────┘ Constructing new sampler... Sampling starts... Sampling starts... Constructing new sampler... Sampling starts... Sampling starts... Constructing new sampler... Sampling starts... Sampling starts... ┌───┬───────┬───────┬────────┬────────┬────────┬────────┬────────┬────────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼───────┼───────┼────────┼────────┼────────┼────────┼────────┼────────┼──────────┼──────────┼───────┤ │ μ │ -0.02 │ 0.208 │ 0.063 │ -0.309 │ -0.191 │ -0.002 │ 0.072 │ 0.542 │ 8.883 │ 39.991 │ 1.434 │ │ σ │ 9.944 │ 0.241 │ 0.071 │ 9.607 │ 9.807 │ 9.955 │ 10.057 │ 10.564 │ 12.216 │ 7.426 │ 1.255 │ └───┴───────┴───────┴────────┴────────┴────────┴────────┴────────┴────────┴──────────┴──────────┴───────┘ ┌───┬──────┬───────┬───────┬────────┬────────┬────────┬────────┬────────┬────────┬──────────┬──────────┬───────┐ │ │ True │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼──────┼───────┼───────┼────────┼────────┼────────┼────────┼────────┼────────┼──────────┼──────────┼───────┤ │ μ │ 0.0 │ -0.02 │ 0.208 │ 0.063 │ -0.309 │ -0.191 │ -0.002 │ 0.072 │ 0.542 │ 8.883 │ 39.991 │ 1.434 │ │ σ │ 10.0 │ 9.944 │ 0.241 │ 0.071 │ 9.607 │ 9.807 │ 9.955 │ 10.057 │ 10.564 │ 12.216 │ 7.426 │ 1.255 │ └───┴──────┴───────┴───────┴────────┴────────┴────────┴────────┴────────┴────────┴──────────┴──────────┴───────┘ Constructing new sampler... Sampling starts... Sampling starts... Constructing new sampler... Sampling starts... Sampling starts... Constructing new sampler... Sampling starts... Sampling starts... ┌───┬───────┬───────┬────────┬────────┬────────┬────────┬────────┬────────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼───────┼───────┼────────┼────────┼────────┼────────┼────────┼────────┼──────────┼──────────┼───────┤ │ μ │ 0.159 │ 0.313 │ 0.121 │ -0.189 │ -0.089 │ -0.009 │ 0.421 │ 0.702 │ 7.311 │ 9.104 │ 1.611 │ │ σ │ 9.884 │ 0.224 │ 0.053 │ 9.634 │ 9.665 │ 9.896 │ 10.013 │ 10.386 │ 18.469 │ 8.508 │ 1.156 │ └───┴───────┴───────┴────────┴────────┴────────┴────────┴────────┴────────┴──────────┴──────────┴───────┘ ┌───┬──────┬───────┬───────┬────────┬────────┬────────┬────────┬────────┬────────┬──────────┬──────────┬───────┐ │ │ True │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼──────┼───────┼───────┼────────┼────────┼────────┼────────┼────────┼────────┼──────────┼──────────┼───────┤ │ μ │ 0.0 │ 0.159 │ 0.313 │ 0.121 │ -0.189 │ -0.089 │ -0.009 │ 0.421 │ 0.702 │ 7.311 │ 9.104 │ 1.611 │ │ σ │ 10.0 │ 9.884 │ 0.224 │ 0.053 │ 9.634 │ 9.665 │ 9.896 │ 10.013 │ 10.386 │ 18.469 │ 8.508 │ 1.156 │ └───┴──────┴───────┴───────┴────────┴────────┴────────┴────────┴────────┴────────┴──────────┴──────────┴───────┘ Constructing new sampler... Sampling starts... Sampling starts... Constructing new sampler... Sampling starts... Sampling starts... Constructing new sampler... Sampling starts... Sampling starts... ┌───┬───────┬───────┬────────┬────────┬────────┬───────┬────────┬────────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼───────┼───────┼────────┼────────┼────────┼───────┼────────┼────────┼──────────┼──────────┼───────┤ │ μ │ 0.073 │ 0.331 │ 0.108 │ -0.453 │ -0.138 │ 0.051 │ 0.305 │ 0.781 │ 9.046 │ 24.321 │ 1.434 │ │ σ │ 9.988 │ 0.232 │ 0.034 │ 9.568 │ 9.782 │ 10.0 │ 10.144 │ 10.502 │ 50.164 │ 102.886 │ 1.066 │ └───┴───────┴───────┴────────┴────────┴────────┴───────┴────────┴────────┴──────────┴──────────┴───────┘ ┌───┬──────┬───────┬───────┬────────┬────────┬────────┬───────┬────────┬────────┬──────────┬──────────┬───────┐ │ │ True │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼──────┼───────┼───────┼────────┼────────┼────────┼───────┼────────┼────────┼──────────┼──────────┼───────┤ │ μ │ 0.0 │ 0.073 │ 0.331 │ 0.108 │ -0.453 │ -0.138 │ 0.051 │ 0.305 │ 0.781 │ 9.046 │ 24.321 │ 1.434 │ │ σ │ 10.0 │ 9.988 │ 0.232 │ 0.034 │ 9.568 │ 9.782 │ 10.0 │ 10.144 │ 10.502 │ 50.164 │ 102.886 │ 1.066 │ └───┴──────┴───────┴───────┴────────┴────────┴────────┴───────┴────────┴────────┴──────────┴──────────┴───────┘ Constructing new sampler... Sampling starts... Sampling starts... Constructing new sampler... Sampling starts... Sampling starts... Constructing new sampler... Sampling starts... Sampling starts... ┌───┬────────┬───────┬────────┬────────┬────────┬───────┬────────┬────────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼────────┼───────┼────────┼────────┼────────┼───────┼────────┼────────┼──────────┼──────────┼───────┤ │ μ │ 0.059 │ 0.439 │ 0.137 │ -0.533 │ -0.312 │ 0.017 │ 0.28 │ 1.099 │ 11.291 │ 26.6 │ 1.311 │ │ σ │ 10.021 │ 0.257 │ 0.027 │ 9.625 │ 9.792 │ 10.02 │ 10.229 │ 10.518 │ 86.933 │ 53.323 │ 1.048 │ └───┴────────┴───────┴────────┴────────┴────────┴───────┴────────┴────────┴──────────┴──────────┴───────┘ ┌───┬──────┬────────┬───────┬────────┬────────┬────────┬───────┬────────┬────────┬──────────┬──────────┬───────┐ │ │ True │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼──────┼────────┼───────┼────────┼────────┼────────┼───────┼────────┼────────┼──────────┼──────────┼───────┤ │ μ │ 0.0 │ 0.059 │ 0.439 │ 0.137 │ -0.533 │ -0.312 │ 0.017 │ 0.28 │ 1.099 │ 11.291 │ 26.6 │ 1.311 │ │ σ │ 10.0 │ 10.021 │ 0.257 │ 0.027 │ 9.625 │ 9.792 │ 10.02 │ 10.229 │ 10.518 │ 86.933 │ 53.323 │ 1.048 │ └───┴──────┴────────┴───────┴────────┴────────┴────────┴───────┴────────┴────────┴──────────┴──────────┴───────┘ Constructing new sampler... Sampling starts... Sampling starts... Constructing new sampler... Sampling starts... Sampling starts... Constructing new sampler... Sampling starts... Sampling starts... ┌───┬───────┬───────┬────────┬────────┬────────┬────────┬────────┬────────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼───────┼───────┼────────┼────────┼────────┼────────┼────────┼────────┼──────────┼──────────┼───────┤ │ μ │ 0.035 │ 0.296 │ 0.072 │ -0.357 │ -0.158 │ -0.057 │ 0.165 │ 0.884 │ 17.458 │ 22.054 │ 1.248 │ │ σ │ 10.01 │ 0.292 │ 0.051 │ 9.517 │ 9.826 │ 9.978 │ 10.239 │ 10.576 │ 34.269 │ 18.801 │ 1.101 │ └───┴───────┴───────┴────────┴────────┴────────┴────────┴────────┴────────┴──────────┴──────────┴───────┘ ┌───┬──────┬───────┬───────┬────────┬────────┬────────┬────────┬────────┬────────┬──────────┬──────────┬───────┐ │ │ True │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼──────┼───────┼───────┼────────┼────────┼────────┼────────┼────────┼────────┼──────────┼──────────┼───────┤ │ μ │ 0.0 │ 0.035 │ 0.296 │ 0.072 │ -0.357 │ -0.158 │ -0.057 │ 0.165 │ 0.884 │ 17.458 │ 22.054 │ 1.248 │ │ σ │ 10.0 │ 10.01 │ 0.292 │ 0.051 │ 9.517 │ 9.826 │ 9.978 │ 10.239 │ 10.576 │ 34.269 │ 18.801 │ 1.101 │ └───┴──────┴───────┴───────┴────────┴────────┴────────┴────────┴────────┴────────┴──────────┴──────────┴───────┘ Constructing new sampler... Sampling starts... Sampling starts... Constructing new sampler... Sampling starts... Sampling starts... Constructing new sampler... Sampling starts... Sampling starts... ┌───┬────────┬───────┬────────┬────────┬────────┬────────┬────────┬────────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼────────┼───────┼────────┼────────┼────────┼────────┼────────┼────────┼──────────┼──────────┼───────┤ │ μ │ 0.201 │ 0.322 │ 0.104 │ -0.265 │ -0.045 │ 0.135 │ 0.442 │ 0.864 │ 9.178 │ 25.627 │ 1.405 │ │ σ │ 10.036 │ 0.286 │ 0.031 │ 9.527 │ 9.838 │ 10.006 │ 10.247 │ 10.631 │ 93.295 │ 39.558 │ 1.204 │ └───┴────────┴───────┴────────┴────────┴────────┴────────┴────────┴────────┴──────────┴──────────┴───────┘ ┌───┬──────┬────────┬───────┬────────┬────────┬────────┬────────┬────────┬────────┬──────────┬──────────┬───────┐ │ │ True │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼──────┼────────┼───────┼────────┼────────┼────────┼────────┼────────┼────────┼──────────┼──────────┼───────┤ │ μ │ 0.0 │ 0.201 │ 0.322 │ 0.104 │ -0.265 │ -0.045 │ 0.135 │ 0.442 │ 0.864 │ 9.178 │ 25.627 │ 1.405 │ │ σ │ 10.0 │ 10.036 │ 0.286 │ 0.031 │ 9.527 │ 9.838 │ 10.006 │ 10.247 │ 10.631 │ 93.295 │ 39.558 │ 1.204 │ └───┴──────┴────────┴───────┴────────┴────────┴────────┴────────┴────────┴────────┴──────────┴──────────┴───────┘ Constructing new sampler... Sampling starts... Sampling starts... Constructing new sampler... Sampling starts... Sampling starts... Constructing new sampler... Sampling starts... Sampling finished, printing diagnostics and saving trace. ##################################################################################### ########################################## Chain 1: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 500 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1080.002, Avg. final ℓposterior: -3737.283. NUTS sampler had 37 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 22.642 (15) number of steps and depth of 3.45 (4). Divergences in: Warmup: 37, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ┌───┬────────┬───────┬────────┬────────┬───────┬────────┬────────┬────────┬──────────┬──────────┬──────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼────────┼───────┼────────┼────────┼───────┼────────┼────────┼────────┼──────────┼──────────┼──────┤ │ μ │ 0.252 │ 0.313 │ 0.04 │ -0.293 │ 0.008 │ 0.252 │ 0.458 │ 0.949 │ NaN │ NaN │ NaN │ │ σ │ 10.027 │ 0.211 │ 0.013 │ 9.635 │ 9.891 │ 10.019 │ 10.202 │ 10.438 │ NaN │ NaN │ NaN │ └───┴────────┴───────┴────────┴────────┴───────┴────────┴────────┴────────┴──────────┴──────────┴──────┘ Sampling starts... Sampling finished, printing diagnostics. ##################################################################################### ########################################## Chain 1: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 100 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1080.486, Avg. final ℓposterior: -3734.96. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 20.86 (27) number of steps and depth of 3.78 (4). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ┌───┬───────┬───────┬────────┬────────┬───────┬───────┬────────┬────────┬──────────┬──────────┬──────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼───────┼───────┼────────┼────────┼───────┼───────┼────────┼────────┼──────────┼──────────┼──────┤ │ μ │ 0.328 │ 0.371 │ 0.073 │ -0.268 │ 0.083 │ 0.239 │ 0.61 │ 1.055 │ NaN │ NaN │ NaN │ │ σ │ 9.98 │ 0.224 │ 0.029 │ 9.558 │ 9.839 │ 9.96 │ 10.144 │ 10.375 │ NaN │ NaN │ NaN │ └───┴───────┴───────┴────────┴────────┴───────┴───────┴────────┴────────┴──────────┴──────────┴──────┘ Constructing new sampler... Sampling starts... Sampling finished, printing diagnostics and saving trace. ##################################################################################### ########################################## Chain 1: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 500 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1079.823, Avg. final ℓposterior: -3738.829. NUTS sampler had 29 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 18.946 (7) number of steps and depth of 3.438 (3). Divergences in: Warmup: 29, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ##################################################################################### ########################################## Chain 1: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 500 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1080.344, Avg. final ℓposterior: -3738.273. NUTS sampler had 28 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 19.216 (15) number of steps and depth of 3.42 (4). Divergences in: Warmup: 28, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ┌───┬────────┬───────┬────────┬────────┬───────┬────────┬────────┬────────┬──────────┬──────────┬──────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼────────┼───────┼────────┼────────┼───────┼────────┼────────┼────────┼──────────┼──────────┼──────┤ │ μ │ 0.237 │ 0.29 │ 0.037 │ -0.318 │ 0.034 │ 0.242 │ 0.431 │ 0.84 │ NaN │ NaN │ NaN │ │ σ │ 10.023 │ 0.209 │ 0.011 │ 9.603 │ 9.876 │ 10.037 │ 10.164 │ 10.436 │ NaN │ NaN │ NaN │ └───┴────────┴───────┴────────┴────────┴───────┴────────┴────────┴────────┴──────────┴──────────┴──────┘ Sampling starts... Sampling finished, printing diagnostics. ##################################################################################### ########################################## Chain 1: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 100 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1080.344, Avg. final ℓposterior: -3735.25. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 23.02 (15) number of steps and depth of 3.92 (4). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ##################################################################################### ########################################## Chain 1: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 100 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1080.031, Avg. final ℓposterior: -3735.152. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 20.72 (7) number of steps and depth of 3.71 (3). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ┌───┬────────┬───────┬────────┬────────┬───────┬────────┬────────┬────────┬──────────┬──────────┬──────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼────────┼───────┼────────┼────────┼───────┼────────┼────────┼────────┼──────────┼──────────┼──────┤ │ μ │ 0.27 │ 0.303 │ 0.035 │ -0.273 │ 0.053 │ 0.259 │ 0.471 │ 0.814 │ NaN │ NaN │ NaN │ │ σ │ 10.035 │ 0.278 │ 0.026 │ 9.499 │ 9.841 │ 10.044 │ 10.205 │ 10.609 │ NaN │ NaN │ NaN │ └───┴────────┴───────┴────────┴────────┴───────┴────────┴────────┴────────┴──────────┴──────────┴──────┘ Constructing new sampler... Sampling starts... Sampling finished, printing diagnostics and saving trace. ##################################################################################### ########################################## Chain 1: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 500 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -0.001, Avg. final ℓposterior: -3735.56. NUTS sampler had 172 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 48.126 (7) number of steps and depth of 2.5 (3). Divergences in: Warmup: 34, Adaptionˢˡᵒʷ: 138, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 2: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 500 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -0.004, Avg. final ℓposterior: -3735.404. NUTS sampler had 75 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 106.748 (15) number of steps and depth of 3.496 (3). Divergences in: Warmup: 25, Adaptionˢˡᵒʷ: 50, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 3: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 500 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -0.001, Avg. final ℓposterior: -3735.638. NUTS sampler had 211 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 24.924 (1) number of steps and depth of 2.004 (0). Divergences in: Warmup: 36, Adaptionˢˡᵒʷ: 175, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 4: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 500 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1.827, Avg. final ℓposterior: -3735.311. NUTS sampler had 69 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 96.32 (15) number of steps and depth of 3.736 (3). Divergences in: Warmup: 19, Adaptionˢˡᵒʷ: 50, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ┌───┬─────────┬─────────┬─────────┬──────────┬────────┬────────┬────────┬────────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼─────────┼─────────┼─────────┼──────────┼────────┼────────┼────────┼────────┼──────────┼──────────┼───────┤ │ μ │ -15.509 │ 69.232 │ 27.937 │ -174.358 │ -0.012 │ 0.349 │ 2.852 │ 52.197 │ 7.32 │ 12.744 │ 1.679 │ │ σ │ 2142.26 │ 42524.1 │ 1258.54 │ 9.64 │ 10.014 │ 10.193 │ 33.407 │ 653.68 │ 8.805 │ 89.617 │ 1.588 │ └───┴─────────┴─────────┴─────────┴──────────┴────────┴────────┴────────┴────────┴──────────┴──────────┴───────┘ Sampling starts... Sampling finished, printing diagnostics. ##################################################################################### ########################################## Chain 1: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 100 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -0.001, Avg. final ℓposterior: -3738.68. NUTS sampler had 25 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 199.06 (1) number of steps and depth of 3.78 (0). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 25, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 2: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 100 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -0.015, Avg. final ℓposterior: -3735.742. NUTS sampler had 15 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 247.04 (2) number of steps and depth of 4.85 (1). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 15, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 3: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 100 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -0.779, Avg. final ℓposterior: -5864.068. NUTS sampler had 68 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 49.27 (1) number of steps and depth of 1.48 (0). Divergences in: Warmup: 43, Adaptionˢˡᵒʷ: 25, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 4: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 100 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -0.001, Avg. final ℓposterior: -4436.643. NUTS sampler had 25 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 257.44 (1) number of steps and depth of 4.08 (0). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 25, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ┌───┬─────────┬───────────┬─────────┬─────────┬────────┬────────┬────────┬─────────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼─────────┼───────────┼─────────┼─────────┼────────┼────────┼────────┼─────────┼──────────┼──────────┼───────┤ │ μ │ 76.445 │ 345.66 │ 73.265 │ -24.356 │ 0.414 │ 15.026 │ 37.974 │ 819.028 │ 11.618 │ 29.818 │ 1.671 │ │ σ │ 18519.2 │ 2.29535e5 │ 15016.9 │ 3.825 │ 10.183 │ 19.998 │ 33.019 │ 34345.4 │ 11.687 │ 37.74 │ 1.467 │ └───┴─────────┴───────────┴─────────┴─────────┴────────┴────────┴────────┴─────────┴──────────┴──────────┴───────┘ Constructing new sampler... Sampling starts... Sampling finished, printing diagnostics and saving trace. ##################################################################################### ########################################## Chain 1: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 500 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -0.029, Avg. final ℓposterior: -3737.415. NUTS sampler had 68 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 102.658 (23) number of steps and depth of 3.718 (4). Divergences in: Warmup: 18, Adaptionˢˡᵒʷ: 50, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 2: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 500 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -0.005, Avg. final ℓposterior: -3736.398. NUTS sampler had 85 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 106.268 (15) number of steps and depth of 3.872 (4). Divergences in: Warmup: 35, Adaptionˢˡᵒʷ: 50, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 3: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 500 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -0.001, Avg. final ℓposterior: -3735.513. NUTS sampler had 86 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 101.258 (15) number of steps and depth of 3.56 (3). Divergences in: Warmup: 36, Adaptionˢˡᵒʷ: 50, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 4: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 500 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -0.331, Avg. final ℓposterior: -3736.888. NUTS sampler had 75 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 120.826 (7) number of steps and depth of 3.984 (3). Divergences in: Warmup: 25, Adaptionˢˡᵒʷ: 50, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ##################################################################################### ########################################## Chain 1: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 500 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -0.002, Avg. final ℓposterior: -3738.438. NUTS sampler had 69 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 95.924 (31) number of steps and depth of 3.678 (4). Divergences in: Warmup: 19, Adaptionˢˡᵒʷ: 50, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 2: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 500 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -0.005, Avg. final ℓposterior: -3739.146. NUTS sampler had 85 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 112.942 (15) number of steps and depth of 3.916 (4). Divergences in: Warmup: 35, Adaptionˢˡᵒʷ: 50, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 3: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 500 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -0.01, Avg. final ℓposterior: -3735.581. NUTS sampler had 86 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 99.988 (15) number of steps and depth of 3.558 (3). Divergences in: Warmup: 36, Adaptionˢˡᵒʷ: 50, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 4: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 500 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -0.176, Avg. final ℓposterior: -3735.901. NUTS sampler had 74 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 111.43 (31) number of steps and depth of 3.968 (4). Divergences in: Warmup: 24, Adaptionˢˡᵒʷ: 50, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ┌───┬─────────┬─────────┬─────────┬────────┬────────┬────────┬────────┬─────────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼─────────┼─────────┼─────────┼────────┼────────┼────────┼────────┼─────────┼──────────┼──────────┼───────┤ │ μ │ 3.144 │ 45.262 │ 4.604 │ -6.625 │ -0.016 │ 0.273 │ 0.552 │ 4.376 │ 48.488 │ 18.811 │ 1.128 │ │ σ │ 2633.99 │ 55242.9 │ 1971.18 │ 9.461 │ 9.873 │ 10.068 │ 10.312 │ 351.801 │ 32.904 │ 18.352 │ 1.083 │ └───┴─────────┴─────────┴─────────┴────────┴────────┴────────┴────────┴─────────┴──────────┴──────────┴───────┘ Sampling starts... Sampling finished, printing diagnostics. ##################################################################################### ########################################## Chain 1: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 100 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -0.001, Avg. final ℓposterior: -3735.42. NUTS sampler had 25 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 276.12 (1) number of steps and depth of 4.75 (0). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 25, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 2: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 100 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -0.001, Avg. final ℓposterior: -3736.505. NUTS sampler had 25 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 225.06 (1) number of steps and depth of 4.3 (0). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 25, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 3: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 100 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -0.001, Avg. final ℓposterior: -3736.044. NUTS sampler had 25 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 254.76 (1) number of steps and depth of 4.51 (0). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 25, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 4: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 100 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -0.001, Avg. final ℓposterior: -3739.437. NUTS sampler had 24 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 266.03 (1) number of steps and depth of 4.64 (0). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 24, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ##################################################################################### ########################################## Chain 1: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 100 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -0.001, Avg. final ℓposterior: -3735.42. NUTS sampler had 25 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 266.94 (1) number of steps and depth of 4.77 (0). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 25, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 2: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 100 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -0.001, Avg. final ℓposterior: -3736.505. NUTS sampler had 25 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 237.56 (1) number of steps and depth of 4.4 (0). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 25, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 3: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 100 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -0.001, Avg. final ℓposterior: -3736.044. NUTS sampler had 25 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 254.86 (1) number of steps and depth of 4.62 (0). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 25, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 4: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 100 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -0.001, Avg. final ℓposterior: -3739.437. NUTS sampler had 25 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 257.69 (1) number of steps and depth of 4.53 (0). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 25, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ┌───┬─────────┬─────────┬─────────┬──────────┬────────┬────────┬────────┬─────────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼─────────┼─────────┼─────────┼──────────┼────────┼────────┼────────┼─────────┼──────────┼──────────┼───────┤ │ μ │ -13.764 │ 35.177 │ 7.668 │ -111.726 │ -0.579 │ 0.164 │ 0.733 │ 16.047 │ 39.367 │ 63.118 │ 1.528 │ │ σ │ 5894.78 │ 64537.7 │ 4496.58 │ 9.196 │ 9.953 │ 10.184 │ 17.247 │ 22343.7 │ 18.742 │ 71.73 │ 1.465 │ └───┴─────────┴─────────┴─────────┴──────────┴────────┴────────┴────────┴─────────┴──────────┴──────────┴───────┘ Constructing new sampler... Sampling starts... Sampling finished, printing diagnostics and saving trace. ##################################################################################### ########################################## Chain 1: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 500 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1867.88, Avg. final ℓposterior: -3735.647. NUTS sampler had 25 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 24.838 (31) number of steps and depth of 3.506 (5). Divergences in: Warmup: 25, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ┌───┬────────┬───────┬────────┬────────┬────────┬────────┬────────┬────────┬──────────┬──────────┬──────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼────────┼───────┼────────┼────────┼────────┼────────┼────────┼────────┼──────────┼──────────┼──────┤ │ μ │ 0.187 │ 0.281 │ 0.033 │ -0.306 │ -0.023 │ 0.163 │ 0.366 │ 0.746 │ NaN │ NaN │ NaN │ │ σ │ 10.017 │ 0.207 │ 0.015 │ 9.603 │ 9.869 │ 10.032 │ 10.143 │ 10.446 │ NaN │ NaN │ NaN │ └───┴────────┴───────┴────────┴────────┴────────┴────────┴────────┴────────┴──────────┴──────────┴──────┘ Sampling starts... Sampling finished, printing diagnostics. ##################################################################################### ########################################## Chain 1: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 100 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -3735.61, Avg. final ℓposterior: -3735.429. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 19.12 (15) number of steps and depth of 3.65 (4). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ┌───┬────────┬───────┬────────┬────────┬───────┬────────┬────────┬────────┬──────────┬──────────┬──────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼────────┼───────┼────────┼────────┼───────┼────────┼────────┼────────┼──────────┼──────────┼──────┤ │ μ │ 0.318 │ 0.263 │ 0.043 │ -0.137 │ 0.157 │ 0.289 │ 0.46 │ 0.847 │ NaN │ NaN │ NaN │ │ σ │ 10.019 │ 0.188 │ 0.019 │ 9.669 │ 9.902 │ 10.003 │ 10.157 │ 10.394 │ NaN │ NaN │ NaN │ └───┴────────┴───────┴────────┴────────┴───────┴────────┴────────┴────────┴──────────┴──────────┴──────┘ Constructing new sampler... Sampling starts... Sampling finished, printing diagnostics and saving trace. ##################################################################################### ########################################## Chain 1: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 500 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1868.228, Avg. final ℓposterior: -3735.385. NUTS sampler had 36 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 16.882 (15) number of steps and depth of 3.266 (4). Divergences in: Warmup: 36, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ##################################################################################### ########################################## Chain 1: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 500 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1868.233, Avg. final ℓposterior: -3736.682. NUTS sampler had 29 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 18.138 (31) number of steps and depth of 3.358 (4). Divergences in: Warmup: 29, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ┌───┬────────┬───────┬────────┬────────┬───────┬───────┬────────┬────────┬──────────┬──────────┬──────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼────────┼───────┼────────┼────────┼───────┼───────┼────────┼────────┼──────────┼──────────┼──────┤ │ μ │ 0.268 │ 0.292 │ 0.037 │ -0.278 │ 0.038 │ 0.294 │ 0.463 │ 0.798 │ NaN │ NaN │ NaN │ │ σ │ 10.011 │ 0.217 │ 0.012 │ 9.61 │ 9.853 │ 9.992 │ 10.176 │ 10.433 │ NaN │ NaN │ NaN │ └───┴────────┴───────┴────────┴────────┴───────┴───────┴────────┴────────┴──────────┴──────────┴──────┘ Sampling starts... Sampling finished, printing diagnostics. ##################################################################################### ########################################## Chain 1: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 100 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -3736.187, Avg. final ℓposterior: -3738.659. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 18.32 (3) number of steps and depth of 3.54 (2). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ##################################################################################### ########################################## Chain 1: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 100 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -3735.304, Avg. final ℓposterior: -3735.755. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 20.42 (9) number of steps and depth of 3.77 (3). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ┌───┬───────┬───────┬────────┬────────┬───────┬────────┬────────┬────────┬──────────┬──────────┬──────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼───────┼───────┼────────┼────────┼───────┼────────┼────────┼────────┼──────────┼──────────┼──────┤ │ μ │ 0.283 │ 0.275 │ 0.032 │ -0.259 │ 0.097 │ 0.291 │ 0.427 │ 0.812 │ NaN │ NaN │ NaN │ │ σ │ 10.04 │ 0.251 │ 0.026 │ 9.487 │ 9.894 │ 10.064 │ 10.214 │ 10.502 │ NaN │ NaN │ NaN │ └───┴───────┴───────┴────────┴────────┴───────┴────────┴────────┴────────┴──────────┴──────────┴──────┘ Constructing new sampler... Sampling starts... Sampling finished, printing diagnostics and saving trace. ##################################################################################### ########################################## Chain 1: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 500 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1867.88, Avg. final ℓposterior: -2588.564. NUTS sampler had 28 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 20.842 (23) number of steps and depth of 3.518 (4). Divergences in: Warmup: 28, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 2: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 500 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1867.88, Avg. final ℓposterior: -2588.5. NUTS sampler had 26 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 21.144 (23) number of steps and depth of 3.494 (4). Divergences in: Warmup: 26, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 3: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 500 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1868.178, Avg. final ℓposterior: -2590.226. NUTS sampler had 24 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 19.452 (7) number of steps and depth of 3.326 (3). Divergences in: Warmup: 24, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 4: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 500 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1867.88, Avg. final ℓposterior: -2588.573. NUTS sampler had 29 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 17.468 (15) number of steps and depth of 3.31 (4). Divergences in: Warmup: 29, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ┌───┬────────┬───────┬────────┬────────┬───────┬───────┬────────┬────────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼────────┼───────┼────────┼────────┼───────┼───────┼────────┼────────┼──────────┼──────────┼───────┤ │ μ │ 0.285 │ 0.349 │ 0.018 │ -0.431 │ 0.058 │ 0.28 │ 0.52 │ 0.964 │ 388.056 │ 583.59 │ 1.014 │ │ σ │ 10.006 │ 0.276 │ 0.014 │ 9.493 │ 9.806 │ 10.0 │ 10.195 │ 10.575 │ 374.169 │ 922.418 │ 1.013 │ └───┴────────┴───────┴────────┴────────┴───────┴───────┴────────┴────────┴──────────┴──────────┴───────┘ Sampling starts... Sampling finished, printing diagnostics. ##################################################################################### ########################################## Chain 1: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 100 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -2589.606, Avg. final ℓposterior: -2696.976. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 20.82 (31) number of steps and depth of 3.77 (4). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 2: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 100 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -2590.039, Avg. final ℓposterior: -2696.732. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 17.52 (15) number of steps and depth of 3.57 (4). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 3: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 100 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -2589.948, Avg. final ℓposterior: -2696.316. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 19.34 (13) number of steps and depth of 3.59 (3). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 4: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 100 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -2589.697, Avg. final ℓposterior: -2695.548. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 17.82 (31) number of steps and depth of 3.56 (4). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ┌───┬───────┬───────┬────────┬────────┬───────┬────────┬────────┬────────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼───────┼───────┼────────┼────────┼───────┼────────┼────────┼────────┼──────────┼──────────┼───────┤ │ μ │ 0.284 │ 0.337 │ 0.036 │ -0.349 │ 0.061 │ 0.287 │ 0.517 │ 0.907 │ 85.733 │ 171.701 │ 1.031 │ │ σ │ 10.02 │ 0.27 │ 0.014 │ 9.474 │ 9.841 │ 10.024 │ 10.199 │ 10.575 │ 355.182 │ 192.684 │ 1.03 │ └───┴───────┴───────┴────────┴────────┴───────┴────────┴────────┴────────┴──────────┴──────────┴───────┘ Constructing new sampler... Sampling starts... Sampling finished, printing diagnostics and saving trace. ##################################################################################### ########################################## Chain 1: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 500 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1867.88, Avg. final ℓposterior: -2588.489. NUTS sampler had 22 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 17.536 (7) number of steps and depth of 3.292 (3). Divergences in: Warmup: 22, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 2: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 500 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1867.88, Avg. final ℓposterior: -2588.339. NUTS sampler had 22 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 18.106 (15) number of steps and depth of 3.332 (4). Divergences in: Warmup: 22, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 3: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 500 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1867.88, Avg. final ℓposterior: -2588.986. NUTS sampler had 22 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 17.84 (15) number of steps and depth of 3.318 (4). Divergences in: Warmup: 22, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 4: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 500 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1867.88, Avg. final ℓposterior: -2588.669. NUTS sampler had 26 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 17.334 (31) number of steps and depth of 3.3 (4). Divergences in: Warmup: 26, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ##################################################################################### ########################################## Chain 1: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 500 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1867.88, Avg. final ℓposterior: -2589.687. NUTS sampler had 23 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 16.752 (11) number of steps and depth of 3.278 (3). Divergences in: Warmup: 23, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 2: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 500 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1867.801, Avg. final ℓposterior: -2588.782. NUTS sampler had 19 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 17.824 (11) number of steps and depth of 3.336 (3). Divergences in: Warmup: 19, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 3: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 500 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1868.501, Avg. final ℓposterior: -2588.985. NUTS sampler had 20 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 18.64 (23) number of steps and depth of 3.31 (4). Divergences in: Warmup: 20, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 4: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 500 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1867.88, Avg. final ℓposterior: -2588.485. NUTS sampler had 34 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 16.652 (15) number of steps and depth of 3.272 (3). Divergences in: Warmup: 34, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ┌───┬────────┬───────┬────────┬────────┬───────┬────────┬────────┬────────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼────────┼───────┼────────┼────────┼───────┼────────┼────────┼────────┼──────────┼──────────┼───────┤ │ μ │ 0.274 │ 0.37 │ 0.016 │ -0.454 │ 0.021 │ 0.274 │ 0.518 │ 1.013 │ 546.633 │ 802.682 │ 1.008 │ │ σ │ 10.034 │ 0.283 │ 0.007 │ 9.489 │ 9.839 │ 10.018 │ 10.219 │ 10.601 │ 1570.13 │ 1273.3 │ 1.001 │ └───┴────────┴───────┴────────┴────────┴───────┴────────┴────────┴────────┴──────────┴──────────┴───────┘ Sampling starts... Sampling finished, printing diagnostics. ##################################################################################### ########################################## Chain 1: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 100 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -2591.844, Avg. final ℓposterior: -2695.869. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 15.86 (15) number of steps and depth of 3.36 (4). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 2: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 100 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -2589.983, Avg. final ℓposterior: -2696.962. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 18.7 (31) number of steps and depth of 3.7 (4). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 3: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 100 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -2590.994, Avg. final ℓposterior: -2695.538. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 19.92 (31) number of steps and depth of 3.73 (4). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 4: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 100 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -2590.461, Avg. final ℓposterior: -2695.449. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 17.56 (15) number of steps and depth of 3.55 (4). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ##################################################################################### ########################################## Chain 1: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 100 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -2591.856, Avg. final ℓposterior: -2695.742. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 17.1 (11) number of steps and depth of 3.57 (3). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 2: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 100 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -2589.451, Avg. final ℓposterior: -2695.268. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 19.74 (15) number of steps and depth of 3.71 (4). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 3: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 100 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -2590.166, Avg. final ℓposterior: -2695.369. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 20.42 (15) number of steps and depth of 3.72 (4). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 4: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 100 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -2590.713, Avg. final ℓposterior: -2695.509. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 16.42 (15) number of steps and depth of 3.53 (4). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ┌───┬────────┬───────┬────────┬───────┬───────┬────────┬────────┬────────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼────────┼───────┼────────┼───────┼───────┼────────┼────────┼────────┼──────────┼──────────┼───────┤ │ μ │ 0.292 │ 0.342 │ 0.025 │ -0.37 │ 0.062 │ 0.289 │ 0.505 │ 0.938 │ 190.294 │ 268.263 │ 1.006 │ │ σ │ 10.011 │ 0.245 │ 0.011 │ 9.509 │ 9.845 │ 10.007 │ 10.186 │ 10.484 │ 471.792 │ 372.653 │ 1.011 │ └───┴────────┴───────┴────────┴───────┴───────┴────────┴────────┴────────┴──────────┴──────────┴───────┘ Constructing new sampler... Sampling starts... Computing... 0%|▏ | ETA: 0:05:53 ( 0.89 s/it) mcmc: diagnostics iter: 2 logobjective: -3735.7599335028153 Temperature: 1.0 accepted: true acceptancerate: 1.5413158259350118e-85 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 1 ℓH: -3739.129127462438                         Computing... 100%|█████████████████████████| Time: 0:00:02 ( 6.08 ms/it) mcmc: diagnostics iter: 100 logobjective: -3736.6338658551654 Temperature: 1.0 accepted: true acceptancerate: 0.9998606429315371 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 127 ℓH: -3738.885526433838 Sampling finished, printing diagnostics and saving trace. ##################################################################################### ########################################## Chain 1: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -3735.76, Avg. final ℓposterior: -3736.362. NUTS sampler had 27 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 13.156 (95) number of steps and depth of 2.067 (6). Divergences in: Warmup: 27, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 2: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -3735.76, Avg. final ℓposterior: -3735.746. NUTS sampler had 23 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 24.4 (63) number of steps and depth of 2.333 (5). Divergences in: Warmup: 23, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 3: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -3735.369, Avg. final ℓposterior: -3737.944. NUTS sampler had 33 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 10.889 (23) number of steps and depth of 2.011 (4). Divergences in: Warmup: 33, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 4: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -3735.759, Avg. final ℓposterior: -3736.634. NUTS sampler had 18 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 35.067 (127) number of steps and depth of 2.411 (6). Divergences in: Warmup: 18, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ┌───┬────────┬───────┬────────┬────────┬───────┬───────┬────────┬───────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼────────┼───────┼────────┼────────┼───────┼───────┼────────┼───────┼──────────┼──────────┼───────┤ │ μ │ 0.235 │ 0.248 │ 0.05 │ -0.224 │ 0.087 │ 0.177 │ 0.346 │ 0.79 │ 25.168 │ 69.309 │ 1.314 │ │ σ │ 10.025 │ 0.141 │ 0.015 │ 9.708 │ 9.947 │ 10.03 │ 10.113 │ 10.3 │ 79.727 │ 55.197 │ 1.29 │ └───┴────────┴───────┴────────┴────────┴───────┴───────┴────────┴───────┴──────────┴──────────┴───────┘ Sampling starts... Computing... 0%|▏ | ETA: 0:01:29 ( 0.22 s/it) mcmc: diagnostics iter: 102 logobjective: -3735.346450791276 Temperature: 1.0 accepted: true acceptancerate: 0.9998397021701971 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 63 ℓH: -3736.320869236958                         Computing... 33%|████████▎ | ETA: 0:00:01 ( 4.43 ms/it) mcmc: diagnostics iter: 131 logobjective: -3735.8222635332595 Temperature: 1.0 accepted: true acceptancerate: 0.9995368058687182 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 15 ℓH: -3738.450862751124                         Computing... 76%|███████████████████ | ETA: 0:00:00 ( 2.27 ms/it) mcmc: diagnostics iter: 103 logobjective: -3736.486622540677 Temperature: 1.0 accepted: true acceptancerate: 0.9999925612177832 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 127 ℓH: -3736.9143874270703                         Computing... 100%|█████████████████████████| Time: 0:00:00 ( 2.04 ms/it) mcmc: diagnostics iter: 200 logobjective: -3735.3317748247227 Temperature: 1.0 accepted: true acceptancerate: 0.9995247668474742 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 31 ℓH: -3736.1793764087743 Sampling finished, printing diagnostics. ##################################################################################### ########################################## Chain 1: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -3735.545, Avg. final ℓposterior: -3735.487. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 22.089 (15) number of steps and depth of 3.7 (4). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 2: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -3736.106, Avg. final ℓposterior: -3737.223. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 26.578 (23) number of steps and depth of 3.822 (4). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 3: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -3738.886, Avg. final ℓposterior: -3735.393. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 17.933 (7) number of steps and depth of 3.433 (3). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 4: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -3736.272, Avg. final ℓposterior: -3735.332. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 38.133 (31) number of steps and depth of 4.156 (4). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ┌───┬────────┬───────┬────────┬────────┬───────┬────────┬────────┬────────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼────────┼───────┼────────┼────────┼───────┼────────┼────────┼────────┼──────────┼──────────┼───────┤ │ μ │ 0.299 │ 0.337 │ 0.033 │ -0.384 │ 0.074 │ 0.318 │ 0.525 │ 0.942 │ 107.373 │ 116.552 │ 1.046 │ │ σ │ 10.009 │ 0.256 │ 0.02 │ 9.505 │ 9.842 │ 10.008 │ 10.165 │ 10.509 │ 159.094 │ 117.586 │ 1.033 │ └───┴────────┴───────┴────────┴────────┴───────┴────────┴────────┴────────┴──────────┴──────────┴───────┘ Constructing new sampler... Sampling starts... Computing... 0%|▏ | ETA: 0:02:10 ( 0.33 s/it) smc: diagnostics iter: 1000 Avgℓobjective: -3738.4475361328045 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.8235437186907668 generated: nothing generated_algorithm: nothing                   Computing... 58%|██████████████▍ | ETA: 0:00:01 ( 5.67 ms/it) smc: diagnostics iter: 1057 Avgℓobjective: -3738.242007561764 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.40706508752974635 generated: nothing generated_algorithm: nothing                   Computing... 85%|█████████████████████▎ | ETA: 0:00:00 ( 4.12 ms/it) smc: diagnostics iter: 1085 Avgℓobjective: -3738.2242024560246 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: -0.8553023561556464 generated: nothing generated_algorithm: nothing                   Computing... 100%|█████████████████████████| Time: 0:00:01 ( 3.66 ms/it) smc: diagnostics iter: 1099 Avgℓobjective: -3738.3568549150004 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.6424563201373563 generated: nothing generated_algorithm: nothing Sampling finished, printing diagnostics and saving trace. ##################################################################################### SMC algorithm with jitter kernel MCMC Diagnostics: Sampler finished after 90 iterations with average acceptance ratio of 0.0%. Initial average ℓlikelihood per particle: -3738.296, variance: 0.23 Final average ℓlikelihood per particle: -3738.357, variance: 0.489 Total number of jittering steps: 112. Rejuvenations on average every 1.0 step, every 1.0 steps in first half, every 1.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.752, -0.074, 0.285, 0.653, 0.912]. Quantiles for average number rejuvenation steps: [1.0, 1.0, 1.0, 1.0, 2.0]. Quantiles for ESS: [4.0, 4.0, 4.0, 4.0, 4.0] for 4 chains. ┌───┬───────┬───────┬────────┬────────┬───────┬────────┬────────┬────────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼───────┼───────┼────────┼────────┼───────┼────────┼────────┼────────┼──────────┼──────────┼───────┤ │ μ │ 0.316 │ 0.287 │ 0.027 │ -0.289 │ 0.127 │ 0.325 │ 0.513 │ 0.828 │ 112.795 │ 120.72 │ 1.029 │ │ σ │ 10.02 │ 0.222 │ 0.013 │ 9.551 │ 9.881 │ 10.024 │ 10.162 │ 10.461 │ 305.109 │ 250.855 │ 1.017 │ └───┴───────┴───────┴────────┴────────┴───────┴────────┴────────┴────────┴──────────┴──────────┴───────┘ Sampling starts... Computing... 44%|███████████▏ | ETA: 0:00:00 ( 0.74 ms/it) smc: diagnostics iter: 1144 Avgℓobjective: -1577.3218389859812 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.623388026631396 generated: nothing generated_algorithm: nothing                   Computing... 78%|███████████████████▌ | ETA: 0:00:00 ( 1.66 ms/it) smc: diagnostics iter: 1178 Avgℓobjective: -1577.560424631162 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.008371581031281217 generated: nothing generated_algorithm: nothing                   Computing... 88%|██████████████████████▏ | ETA: 0:00:00 ( 1.79 ms/it) smc: diagnostics iter: 1188 Avgℓobjective: -1577.2159432135225 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.7570721644127653 generated: nothing generated_algorithm: nothing                   Computing... 98%|████████████████████████▌| ETA: 0:00:00 ( 1.92 ms/it) smc: diagnostics iter: 1198 Avgℓobjective: -1577.4931720682703 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.5650148773060373 generated: nothing generated_algorithm: nothing                   Computing... 100%|█████████████████████████| Time: 0:00:00 ( 1.91 ms/it) smc: diagnostics iter: 1199 Avgℓobjective: -1577.4523631873776 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.39150549995288364 generated: nothing generated_algorithm: nothing Sampling finished, printing diagnostics. ##################################################################################### SMC algorithm with jitter kernel MCMC Diagnostics: Sampler finished after 90 iterations with average acceptance ratio of 0.0%. Initial average ℓlikelihood per particle: -1576.979, variance: 0.199 Final average ℓlikelihood per particle: -1577.452, variance: 0.235 Total number of jittering steps: 230. Rejuvenations on average every 1.0 step, every 1.0 steps in first half, every 1.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.488, 0.135, 0.534, 0.837, 1.0]. Quantiles for average number rejuvenation steps: [1.0, 1.0, 1.0, 1.0, 10.0]. Quantiles for ESS: [4.0, 4.0, 4.0, 4.0, 4.0] for 4 chains. ┌───┬───────┬───────┬────────┬───────┬───────┬───────┬───────┬───────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼───────┼───────┼────────┼───────┼───────┼───────┼───────┼───────┼──────────┼──────────┼───────┤ │ μ │ 0.029 │ 0.029 │ 0.003 │ -0.02 │ 0.01 │ 0.031 │ 0.046 │ 0.089 │ 140.345 │ 200.857 │ 1.127 │ │ σ │ 1.014 │ 0.024 │ 0.006 │ 0.966 │ 0.997 │ 1.014 │ 1.03 │ 1.062 │ 18.797 │ 26.369 │ 1.201 │ └───┴───────┴───────┴────────┴───────┴───────┴───────┴───────┴───────┴──────────┴──────────┴───────┘ Constructing new sampler... Sampling starts... Computing... 0%| | ETA: 0:08:08 ( 0.61 s/it) smc: diagnostics iter: 1000 Avgℓobjective: -49567.00504540928 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: NaN generated: nothing generated_algorithm: nothing                   Computing... 13%|███▎ | ETA: 0:00:14 (19.49 ms/it) smc: diagnostics iter: 1050 Avgℓobjective: -3738.4913904784617 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.32381700014044307 generated: nothing generated_algorithm: nothing                   Computing... 14%|███▋ | ETA: 0:00:13 (18.41 ms/it) mcmc: diagnostics iter: 58 logobjective: -3735.7961384304726 Temperature: 1.0 accepted: true acceptancerate: 4.310058470789519e-152 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 1 ℓH: -3735.8345173845028                         Computing... 16%|███▉ | ETA: 0:00:12 (18.13 ms/it) mcmc: diagnostics iter: 63 logobjective: -3735.6273286715955 Temperature: 1.0 accepted: true acceptancerate: 2.1258355351578917e-39 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 3 ℓH: -3735.693586165747                         Computing... 16%|████▏ | ETA: 0:00:12 (18.09 ms/it) smc: diagnostics iter: 1065 Avgℓobjective: -3738.820166796746 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.8933903024762655 generated: nothing generated_algorithm: nothing                   Computing... 18%|████▍ | ETA: 0:00:12 (17.84 ms/it) smc: diagnostics iter: 1069 Avgℓobjective: -3738.2096189587382 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: -0.16368614311882201 generated: nothing generated_algorithm: nothing                   Computing... 18%|████▋ | ETA: 0:00:12 (17.99 ms/it) mcmc: diagnostics iter: 74 logobjective: -3736.113627630712 Temperature: 1.0 accepted: true acceptancerate: 2.5095154484002977e-9 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 1 ℓH: -3736.34833893549                         Computing... 19%|████▊ | ETA: 0:00:12 (18.10 ms/it) smc: diagnostics iter: 1075 Avgℓobjective: -3738.274409057747 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.737446707819071 generated: nothing generated_algorithm: nothing                   Computing... 20%|█████▏ | ETA: 0:00:11 (17.68 ms/it) smc: diagnostics iter: 1081 Avgℓobjective: -3737.841958750766 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.4770913297470679 generated: nothing generated_algorithm: nothing                   Computing... 22%|█████▌ | ETA: 0:00:11 (17.34 ms/it) smc: diagnostics iter: 1086 Avgℓobjective: -3738.5696968420425 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: -0.021643718713746873 generated: nothing generated_algorithm: nothing                   Computing... 23%|█████▊ | ETA: 0:00:10 (16.93 ms/it) smc: diagnostics iter: 1092 Avgℓobjective: -3738.3179342287985 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.40945188152970113 generated: nothing generated_algorithm: nothing                   Computing... 24%|██████▏ | ETA: 0:00:10 (16.80 ms/it) mcmc: diagnostics iter: 98 logobjective: -3737.108853958908 Temperature: 1.0 accepted: true acceptancerate: 1.4839358770209613e-13 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 1 ℓH: -3737.2009510321645                         Computing... 25%|██████▎ | ETA: 0:00:10 (16.84 ms/it) smc: diagnostics iter: 1000 Avgℓobjective: -49567.00504540928 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: NaN generated: nothing generated_algorithm: nothing                   Computing... 33%|████████▎ | ETA: 0:00:09 (16.14 ms/it) smc: diagnostics iter: 1030 Avgℓobjective: -4040.3821746182675 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.998873731234952 generated: nothing generated_algorithm: nothing                   Computing... 34%|████████▌ | ETA: 0:00:08 (15.97 ms/it) smc: diagnostics iter: 1035 Avgℓobjective: -3740.564770069686 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: -0.20090795707072917 generated: nothing generated_algorithm: nothing                   Computing... 35%|████████▊ | ETA: 0:00:08 (15.87 ms/it) mcmc: diagnostics iter: 41 logobjective: -3736.0079484181147 Temperature: 1.0 accepted: true acceptancerate: 1.5395289000193322e-89 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 1 ℓH: -3737.303056494266                         Computing... 36%|█████████ | ETA: 0:00:08 (15.79 ms/it) mcmc: diagnostics iter: 45 logobjective: -3735.696499376805 Temperature: 1.0 accepted: true acceptancerate: 1.371014449350392e-47 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 3 ℓH: -3736.4720615126535                         Computing... 37%|█████████▎ | ETA: 0:00:08 (15.91 ms/it) mcmc: diagnostics iter: 49 logobjective: -3735.4950929435718 Temperature: 1.0 accepted: true acceptancerate: 8.620687613443765e-12 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 3 ℓH: -3735.882044129621                         Computing... 39%|█████████▊ | ETA: 0:00:08 (15.73 ms/it) smc: diagnostics iter: 1055 Avgℓobjective: -3738.245478505366 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.7805023667008123 generated: nothing generated_algorithm: nothing                   Computing... 40%|██████████ | ETA: 0:00:08 (15.66 ms/it) smc: diagnostics iter: 1059 Avgℓobjective: -3738.9781806845826 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.24043870559666558 generated: nothing generated_algorithm: nothing                   Computing... 42%|██████████▍ | ETA: 0:00:07 (15.35 ms/it) mcmc: diagnostics iter: 67 logobjective: -3738.0840476136073 Temperature: 1.0 accepted: true acceptancerate: 7.046037258971977e-53 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 3 ℓH: -3739.298058113052                         Computing... 43%|██████████▊ | ETA: 0:00:07 (15.15 ms/it) mcmc: diagnostics iter: 73 logobjective: -3735.942843973224 Temperature: 1.0 accepted: true acceptancerate: 5.26221733140079e-70 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 1 ℓH: -3736.519542140741                         Computing... 44%|███████████▏ | ETA: 0:00:07 (15.11 ms/it) smc: diagnostics iter: 1077 Avgℓobjective: -3738.3042220394445 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: -0.01703644058924325 generated: nothing generated_algorithm: nothing                   Computing... 46%|███████████▍ | ETA: 0:00:07 (15.10 ms/it) smc: diagnostics iter: 1081 Avgℓobjective: -3739.351589775666 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.7574846864129958 generated: nothing generated_algorithm: nothing                   Computing... 48%|████████████ | ETA: 0:00:06 (14.73 ms/it) mcmc: diagnostics iter: 92 logobjective: -3737.2215721240805 Temperature: 1.0 accepted: true acceptancerate: 4.471028175815961e-25 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 2 ℓH: -3739.243984388894                         Computing... 50%|████████████▌ | ETA: 0:00:06 (14.45 ms/it) smc: diagnostics iter: 1098 Avgℓobjective: -3738.7408401090943 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.43183987419478453 generated: nothing generated_algorithm: nothing                   Computing... 64%|████████████████ | ETA: 0:00:04 (13.15 ms/it) smc: diagnostics iter: 1056 Avgℓobjective: -3738.332849980499 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.20419162988239148 generated: nothing generated_algorithm: nothing                   Computing... 66%|████████████████▌ | ETA: 0:00:04 (13.23 ms/it) smc: diagnostics iter: 1062 Avgℓobjective: -3738.358990863585 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.4317547077659636 generated: nothing generated_algorithm: nothing                   Computing... 66%|████████████████▋ | ETA: 0:00:04 (13.34 ms/it) smc: diagnostics iter: 1065 Avgℓobjective: -3738.522233989148 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.5291653872329067 generated: nothing generated_algorithm: nothing                   Computing... 67%|████████████████▊ | ETA: 0:00:04 (13.43 ms/it) smc: diagnostics iter: 1068 Avgℓobjective: -3738.31680571597 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.04358113241212491 generated: nothing generated_algorithm: nothing                   Computing... 69%|█████████████████▏ | ETA: 0:00:03 (13.44 ms/it) mcmc: diagnostics iter: 75 logobjective: -3737.4317052986707 Temperature: 1.0 accepted: true acceptancerate: 1.7294646422222613e-293 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 1 ℓH: -3738.808067715087                         Computing... 70%|█████████████████▍ | ETA: 0:00:03 (13.54 ms/it) smc: diagnostics iter: 1077 Avgℓobjective: -3739.25499170731 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.9317734295124671 generated: nothing generated_algorithm: nothing                   Computing... 70%|█████████████████▌ | ETA: 0:00:03 (13.61 ms/it) smc: diagnostics iter: 1080 Avgℓobjective: -3738.2491953209483 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.17089536189280302 generated: nothing generated_algorithm: nothing                   Computing... 71%|█████████████████▊ | ETA: 0:00:03 (13.63 ms/it) mcmc: diagnostics iter: 85 logobjective: -3735.465699002331 Temperature: 1.0 accepted: true acceptancerate: 0.023142407645009494 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 1 ℓH: -3735.6907909574256                         Computing... 72%|██████████████████ | ETA: 0:00:03 (13.71 ms/it) smc: diagnostics iter: 1087 Avgℓobjective: -3738.339500023996 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.5988801668243036 generated: nothing generated_algorithm: nothing                   Computing... 73%|██████████████████▎ | ETA: 0:00:03 (13.77 ms/it) smc: diagnostics iter: 1090 Avgℓobjective: -3738.440030566454 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.22477826209850216 generated: nothing generated_algorithm: nothing                   Computing... 74%|██████████████████▍ | ETA: 0:00:03 (13.85 ms/it) smc: diagnostics iter: 1093 Avgℓobjective: -3738.1599612094083 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.8717549798298896 generated: nothing generated_algorithm: nothing                   Computing... 74%|██████████████████▋ | ETA: 0:00:03 (13.97 ms/it) smc: diagnostics iter: 1097 Avgℓobjective: -3738.575428170027 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: -0.2055764976477508 generated: nothing generated_algorithm: nothing                   Computing... 78%|███████████████████▋ | ETA: 0:00:02 (13.42 ms/it) smc: diagnostics iter: 1013 Avgℓobjective: -6840.332979860956 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.5136132128567844 generated: nothing generated_algorithm: nothing                   Computing... 82%|████████████████████▋ | ETA: 0:00:02 (13.84 ms/it) smc: diagnostics iter: 1029 Avgℓobjective: -3739.541517100471 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.7825348984387241 generated: nothing generated_algorithm: nothing                   Computing... 89%|██████████████████████▎ | ETA: 0:00:01 (13.04 ms/it) smc: diagnostics iter: 1054 Avgℓobjective: -3738.6233594872424 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.8962692682252544 generated: nothing generated_algorithm: nothing                   Computing... 94%|███████████████████████▌ | ETA: 0:00:01 (12.62 ms/it) mcmc: diagnostics iter: 76 logobjective: -3737.1158675967313 Temperature: 1.0 accepted: true acceptancerate: 5.922945555066045e-8 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 3 ℓH: -3737.4204020777097                         Computing... 96%|████████████████████████ | ETA: 0:00:00 (12.54 ms/it) smc: diagnostics iter: 1084 Avgℓobjective: -3738.1138982955026 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.502057135660178 generated: nothing generated_algorithm: nothing                   Computing... 98%|████████████████████████▌| ETA: 0:00:00 (12.47 ms/it) smc: diagnostics iter: 1090 Avgℓobjective: -3738.727711657664 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: -0.0815069940580484 generated: nothing generated_algorithm: nothing                   Computing... 99%|████████████████████████▊| ETA: 0:00:00 (12.42 ms/it) smc: diagnostics iter: 1096 Avgℓobjective: -3738.317171028058 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.6535649557837279 generated: nothing generated_algorithm: nothing                   Computing... 100%|█████████████████████████| Time: 0:00:09 (12.41 ms/it) smc: diagnostics iter: 1099 Avgℓobjective: -3738.633580804174 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.14320921224236138 generated: nothing generated_algorithm: nothing Sampling finished, printing diagnostics and saving trace. ##################################################################################### ########################################## Chain 1: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -8898.125, Avg. final ℓposterior: -3735.877. NUTS sampler had 53 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 1.667 (1) number of steps and depth of 0.756 (1). Divergences in: Warmup: 49, Adaptionˢˡᵒʷ: 4, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 2: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -18322.387, Avg. final ℓposterior: -3735.495. NUTS sampler had 49 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 1.656 (3) number of steps and depth of 0.833 (1). Divergences in: Warmup: 45, Adaptionˢˡᵒʷ: 4, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 3: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -8841.796, Avg. final ℓposterior: -3735.719. NUTS sampler had 52 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 1.611 (2) number of steps and depth of 0.8 (1). Divergences in: Warmup: 47, Adaptionˢˡᵒʷ: 5, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 4: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -8110.309, Avg. final ℓposterior: -3738.602. NUTS sampler had 46 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 1.7 (3) number of steps and depth of 0.822 (1). Divergences in: Warmup: 41, Adaptionˢˡᵒʷ: 5, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ##################################################################################### ########################################## Chain 1: SMC Diagnostics: SMC algorithm with jitter kernel MCMC Diagnostics: Sampler finished after 90 iterations with average acceptance ratio of 0.0%. Initial average ℓlikelihood per particle: -9322.816, variance: 1.3211604241e7 Final average ℓlikelihood per particle: -3738.087, variance: 0.115 Total number of jittering steps: 233. Rejuvenations on average every 1.0 step, every 1.0 steps in first half, every 1.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.283, 0.351, 0.64, 0.874, 0.98]. Quantiles for average number rejuvenation steps: [1.0, 1.0, 1.0, 2.75, 10.0]. Quantiles for ESS: [4.0, 4.0, 4.0, 4.0, 4.0] for 4 chains. ########################################## Chain 2: SMC Diagnostics: SMC algorithm with jitter kernel MCMC Diagnostics: Sampler finished after 90 iterations with average acceptance ratio of 0.0%. Initial average ℓlikelihood per particle: -14108.689, variance: 6.5420403255e7 Final average ℓlikelihood per particle: -3739.139, variance: 1.382 Total number of jittering steps: 231. Rejuvenations on average every 1.0 step, every 1.0 steps in first half, every 1.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.196, 0.285, 0.65, 0.869, 0.999]. Quantiles for average number rejuvenation steps: [1.0, 1.0, 1.0, 2.0, 10.0]. Quantiles for ESS: [4.0, 4.0, 4.0, 4.0, 4.0] for 4 chains. ########################################## Chain 3: SMC Diagnostics: SMC algorithm with jitter kernel MCMC Diagnostics: Sampler finished after 90 iterations with average acceptance ratio of 0.0%. Initial average ℓlikelihood per particle: -10097.426, variance: 4.808001518e6 Final average ℓlikelihood per particle: -3738.263, variance: 0.094 Total number of jittering steps: 229. Rejuvenations on average every 1.0 step, every 1.0 steps in first half, every 1.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.693, 0.171, 0.445, 0.876, 0.997]. Quantiles for average number rejuvenation steps: [1.0, 1.0, 1.0, 2.0, 10.0]. Quantiles for ESS: [4.0, 4.0, 4.0, 4.0, 4.0] for 4 chains. ########################################## Chain 4: SMC Diagnostics: SMC algorithm with jitter kernel MCMC Diagnostics: Sampler finished after 90 iterations with average acceptance ratio of 0.0%. Initial average ℓlikelihood per particle: -14653.5, variance: 7.5305226027e7 Final average ℓlikelihood per particle: -3738.634, variance: 0.553 Total number of jittering steps: 179. Rejuvenations on average every 1.0 step, every 1.0 steps in first half, every 1.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.598, 0.21, 0.575, 0.822, 0.971]. Quantiles for average number rejuvenation steps: [1.0, 1.0, 1.0, 2.0, 6.775]. Quantiles for ESS: [4.0, 4.0, 4.0, 4.0, 4.0] for 4 chains. ┌───┬───────┬───────┬────────┬────────┬───────┬───────┬────────┬────────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼───────┼───────┼────────┼────────┼───────┼───────┼────────┼────────┼──────────┼──────────┼───────┤ │ μ │ 0.212 │ 0.262 │ 0.019 │ -0.255 │ 0.045 │ 0.144 │ 0.411 │ 0.738 │ 206.44 │ 242.525 │ 1.052 │ │ σ │ 9.429 │ 2.603 │ 0.344 │ 2.774 │ 9.77 │ 9.978 │ 10.142 │ 10.592 │ 74.85 │ 70.239 │ 1.062 │ └───┴───────┴───────┴────────┴────────┴───────┴───────┴────────┴────────┴──────────┴──────────┴───────┘ Sampling starts... Computing... 0%| | ETA: 0:03:51 ( 0.29 s/it) smc: diagnostics iter: 1100 Avgℓobjective: -3280.1354532730393 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.3123615495583977 generated: nothing generated_algorithm: nothing                   Computing... 3%|▊ | ETA: 0:00:24 (31.03 ms/it) smc: diagnostics iter: 1110 Avgℓobjective: -1649.9093977388834 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.8928502555282556 generated: nothing generated_algorithm: nothing                   Computing... 11%|██▉ | ETA: 0:00:07 ( 9.79 ms/it) mcmc: diagnostics iter: 146 logobjective: -1600.6540703123574 Temperature: 1.0 accepted: true acceptancerate: 6.072538373445042e-13 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 2 ℓH: -1601.0072533330542                         Computing... 16%|███▉ | ETA: 0:00:06 ( 8.15 ms/it) smc: diagnostics iter: 1161 Avgℓobjective: -1601.4532131449787 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.2928832072688775 generated: nothing generated_algorithm: nothing                   Computing... 19%|████▊ | ETA: 0:00:05 ( 7.48 ms/it) smc: diagnostics iter: 1175 Avgℓobjective: -1600.9382001663694 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: -0.358870005533644 generated: nothing generated_algorithm: nothing                   Computing... 23%|█████▋ | ETA: 0:00:04 ( 6.87 ms/it) mcmc: diagnostics iter: 191 logobjective: -1600.4433201710742 Temperature: 1.0 accepted: true acceptancerate: 3.477047298080184e-29 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 1 ℓH: -1601.9009535333887                         Computing... 26%|██████▌ | ETA: 0:00:04 ( 6.51 ms/it) smc: diagnostics iter: 1103 Avgℓobjective: -2500.856811620709 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.9803969540193251 generated: nothing generated_algorithm: nothing                   Computing... 31%|███████▊ | ETA: 0:00:03 ( 5.83 ms/it) smc: diagnostics iter: 1124 Avgℓobjective: -1610.4884402139992 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.9945349621996844 generated: nothing generated_algorithm: nothing                   Computing... 42%|██████████▍ | ETA: 0:00:02 ( 4.86 ms/it) smc: diagnostics iter: 1165 Avgℓobjective: -1601.499798171417 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: -0.0012071028389716854 generated: nothing generated_algorithm: nothing                   Computing... 48%|████████████ | ETA: 0:00:02 ( 4.57 ms/it) smc: diagnostics iter: 1191 Avgℓobjective: -1600.8990581997396 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.06891634882926254 generated: nothing generated_algorithm: nothing                   Computing... 53%|█████████████▎ | ETA: 0:00:02 ( 4.58 ms/it) smc: diagnostics iter: 1110 Avgℓobjective: -1657.9591023432688 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.9948086301886931 generated: nothing generated_algorithm: nothing                   Computing... 62%|███████████████▍ | ETA: 0:00:01 ( 4.15 ms/it) mcmc: diagnostics iter: 147 logobjective: -1601.5849655934203 Temperature: 1.0 accepted: true acceptancerate: 1.9024797596644356e-100 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 1 ℓH: -1601.861006651489                         Computing... 70%|█████████████████▍ | ETA: 0:00:01 ( 3.88 ms/it) smc: diagnostics iter: 1177 Avgℓobjective: -1601.5990837500053 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.2937977070554544 generated: nothing generated_algorithm: nothing                   Computing... 77%|███████████████████▏ | ETA: 0:00:01 ( 3.77 ms/it) mcmc: diagnostics iter: 107 logobjective: -2634.831022062943 Temperature: 1.0 accepted: true acceptancerate: 0.0 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 1 ℓH: -2635.3467646263866                         Computing... 82%|████████████████████▍ | ETA: 0:00:01 ( 3.82 ms/it) smc: diagnostics iter: 1125 Avgℓobjective: -1601.1791425943586 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.9913909112862174 generated: nothing generated_algorithm: nothing                   Computing... 95%|███████████████████████▊ | ETA: 0:00:00 ( 3.64 ms/it) mcmc: diagnostics iter: 180 logobjective: -1600.4657720686557 Temperature: 1.0 accepted: true acceptancerate: 4.0851811961100225e-88 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 1 ℓH: -1601.676596568844                         Computing... 99%|█████████████████████████| ETA: 0:00:00 ( 3.67 ms/it) smc: diagnostics iter: 1198 Avgℓobjective: -1601.3712772088354 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.8407012757865255 generated: nothing generated_algorithm: nothing                   Computing... 100%|█████████████████████████| Time: 0:00:02 ( 3.68 ms/it) smc: diagnostics iter: 1199 Avgℓobjective: -1601.1690435060702 Temperature: 1.0 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.41279358047570686 generated: nothing generated_algorithm: nothing Sampling finished, printing diagnostics. ##################################################################################### ########################################## Chain 1: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1601.331, Avg. final ℓposterior: -1600.529. NUTS sampler had 52 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 1.5 (2) number of steps and depth of 0.733 (1). Divergences in: Warmup: 45, Adaptionˢˡᵒʷ: 7, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 2: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1603.751, Avg. final ℓposterior: -1600.553. NUTS sampler had 54 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 1.489 (1) number of steps and depth of 0.744 (1). Divergences in: Warmup: 49, Adaptionˢˡᵒʷ: 5, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 3: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1600.699, Avg. final ℓposterior: -1601.217. NUTS sampler had 42 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 1.556 (1) number of steps and depth of 0.878 (1). Divergences in: Warmup: 36, Adaptionˢˡᵒʷ: 6, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 4: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1602.291, Avg. final ℓposterior: -1600.686. NUTS sampler had 46 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 1.489 (1) number of steps and depth of 0.789 (1). Divergences in: Warmup: 35, Adaptionˢˡᵒʷ: 11, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ##################################################################################### ########################################## Chain 1: SMC Diagnostics: SMC algorithm with jitter kernel MCMC Diagnostics: Sampler finished after 90 iterations with average acceptance ratio of 0.0%. Initial average ℓlikelihood per particle: -1649.909, variance: 9662.595 Final average ℓlikelihood per particle: -1601.526, variance: 0.48 Total number of jittering steps: 288. Rejuvenations on average every 1.0 step, every 1.0 steps in first half, every 1.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.414, 0.399, 0.799, 0.94, 0.994]. Quantiles for average number rejuvenation steps: [1.0, 1.0, 1.0, 5.0, 10.0]. Quantiles for ESS: [4.0, 4.0, 4.0, 4.0, 4.0] for 4 chains. ########################################## Chain 2: SMC Diagnostics: SMC algorithm with jitter kernel MCMC Diagnostics: Sampler finished after 90 iterations with average acceptance ratio of 0.0%. Initial average ℓlikelihood per particle: -1657.19, variance: 4783.287 Final average ℓlikelihood per particle: -1601.309, variance: 0.474 Total number of jittering steps: 258. Rejuvenations on average every 1.0 step, every 1.0 steps in first half, every 1.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.47, 0.063, 0.63, 0.898, 0.999]. Quantiles for average number rejuvenation steps: [1.0, 1.0, 1.0, 4.0, 10.0]. Quantiles for ESS: [4.0, 4.0, 4.0, 4.0, 4.0] for 4 chains. ########################################## Chain 3: SMC Diagnostics: SMC algorithm with jitter kernel MCMC Diagnostics: Sampler finished after 90 iterations with average acceptance ratio of 0.0%. Initial average ℓlikelihood per particle: -1657.959, variance: 12811.335 Final average ℓlikelihood per particle: -1601.702, variance: 0.235 Total number of jittering steps: 259. Rejuvenations on average every 1.0 step, every 1.0 steps in first half, every 1.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.713, -0.021, 0.603, 0.923, 0.995]. Quantiles for average number rejuvenation steps: [1.0, 1.0, 1.0, 2.0, 10.0]. Quantiles for ESS: [4.0, 4.0, 4.0, 4.0, 4.0] for 4 chains. ########################################## Chain 4: SMC Diagnostics: SMC algorithm with jitter kernel MCMC Diagnostics: Sampler finished after 90 iterations with average acceptance ratio of 0.0%. Initial average ℓlikelihood per particle: -1735.154, variance: 70471.348 Final average ℓlikelihood per particle: -1601.169, variance: 0.566 Total number of jittering steps: 292. Rejuvenations on average every 1.0 step, every 1.0 steps in first half, every 1.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.241, 0.175, 0.713, 0.917, 1.0]. Quantiles for average number rejuvenation steps: [1.0, 1.0, 1.0, 5.0, 10.0]. Quantiles for ESS: [4.0, 4.0, 4.0, 4.0, 4.0] for 4 chains. ┌───┬────────┬───────┬────────┬────────┬────────┬────────┬────────┬───────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼────────┼───────┼────────┼────────┼────────┼────────┼────────┼───────┼──────────┼──────────┼───────┤ │ μ │ -0.026 │ 0.059 │ 0.006 │ -0.113 │ -0.053 │ -0.026 │ -0.004 │ 0.046 │ 266.411 │ 71.617 │ 1.052 │ │ σ │ 1.031 │ 0.092 │ 0.012 │ 0.881 │ 1.018 │ 1.033 │ 1.048 │ 1.086 │ 144.281 │ 59.526 │ 1.083 │ └───┴────────┴───────┴────────┴────────┴────────┴────────┴────────┴───────┴──────────┴──────────┴───────┘ Constructing new sampler... Sampling starts... Computing... 0%|▏ | ETA: 0:02:52 ( 0.43 s/it) mcmc: diagnostics iter: 2 logobjective: -1079.8232668525707 Temperature: 0.289050497374996 accepted: true acceptancerate: 0.31301091036939543 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 3 ℓH: -1080.1907697625957                         Computing... 49%|████████████▎ | ETA: 0:00:01 ( 5.57 ms/it) mcmc: diagnostics iter: 96 logobjective: -3735.380383517753 Temperature: 0.9997965730219448 accepted: true acceptancerate: 0.9997089321191598 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 15 ℓH: -3735.5865563560774                         Computing... 100%|█████████████████████████| Time: 0:00:01 ( 2.93 ms/it) mcmc: diagnostics iter: 100 logobjective: -3735.437336931283 Temperature: 0.9998636296729204 accepted: true acceptancerate: 0.9997278346783417 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 63 ℓH: -3735.678101730642 Sampling finished, printing diagnostics and saving trace. ##################################################################################### ########################################## Chain 1: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1868.144, Avg. final ℓposterior: -3735.373. NUTS sampler had 26 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 18.756 (79) number of steps and depth of 2.144 (6). Divergences in: Warmup: 26, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 2: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1869.526, Avg. final ℓposterior: -3735.303. NUTS sampler had 35 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 59.5 (15) number of steps and depth of 2.4 (3). Divergences in: Warmup: 35, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 3: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1867.649, Avg. final ℓposterior: -3737.345. NUTS sampler had 23 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 11.978 (7) number of steps and depth of 1.944 (3). Divergences in: Warmup: 23, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 4: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1867.745, Avg. final ℓposterior: -3735.437. NUTS sampler had 17 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 10.389 (63) number of steps and depth of 1.933 (5). Divergences in: Warmup: 17, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ┌───┬───────┬───────┬────────┬────────┬───────┬───────┬────────┬────────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼───────┼───────┼────────┼────────┼───────┼───────┼────────┼────────┼──────────┼──────────┼───────┤ │ μ │ 0.155 │ 0.285 │ 0.085 │ -0.405 │ 0.04 │ 0.168 │ 0.299 │ 0.73 │ 11.331 │ 17.963 │ 1.324 │ │ σ │ 9.92 │ 0.272 │ 0.098 │ 9.455 │ 9.793 │ 9.973 │ 10.114 │ 10.318 │ 10.146 │ 5.633 │ 1.389 │ └───┴───────┴───────┴────────┴────────┴───────┴───────┴────────┴────────┴──────────┴──────────┴───────┘ Sampling starts... Computing... 0%|▏ | ETA: 0:01:23 ( 0.21 s/it) mcmc: diagnostics iter: 102 logobjective: -1079.914977697063 Temperature: 0.289050497374996 accepted: true acceptancerate: 0.9998669223347451 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 127 ℓH: -1080.2099676413727                         Computing... 22%|█████▍ | ETA: 0:00:02 ( 6.00 ms/it) mcmc: diagnostics iter: 186 logobjective: -3733.6584978570345 Temperature: 0.9994472213630764 accepted: true acceptancerate: 0.9992465622115136 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 15 ℓH: -3734.325844978015                         Computing... 42%|██████████▌ | ETA: 0:00:01 ( 5.66 ms/it) mcmc: diagnostics iter: 169 logobjective: -3725.5398502459807 Temperature: 0.9969815836752917 accepted: true acceptancerate: 0.9901101333296676 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 15 ℓH: -3727.0565331637326                         Computing... 72%|██████████████████ | ETA: 0:00:00 ( 3.73 ms/it) mcmc: diagnostics iter: 187 logobjective: -3738.4859214800263 Temperature: 0.9994997988929205 accepted: true acceptancerate: 0.964932649963878 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 15 ℓH: -3740.2942896089407                         Computing... 100%|█████████████████████████| Time: 0:00:01 ( 2.89 ms/it) mcmc: diagnostics iter: 200 logobjective: -3739.3863425718487 Temperature: 0.9998636296729204 accepted: true acceptancerate: 0.9883485726842672 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 15 ℓH: -3739.8052124135925 Sampling finished, printing diagnostics. ##################################################################################### ########################################## Chain 1: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1868.376, Avg. final ℓposterior: -3734.964. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 26.222 (15) number of steps and depth of 3.889 (4). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 2: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1868.224, Avg. final ℓposterior: -3735.511. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 80.933 (29) number of steps and depth of 4.3 (4). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 3: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1868.899, Avg. final ℓposterior: -3735.32. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 26.889 (39) number of steps and depth of 4.089 (5). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 4: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1869.48, Avg. final ℓposterior: -3739.386. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 18.356 (15) number of steps and depth of 3.578 (4). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ┌───┬────────┬───────┬────────┬────────┬───────┬────────┬────────┬────────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼────────┼───────┼────────┼────────┼───────┼────────┼────────┼────────┼──────────┼──────────┼───────┤ │ μ │ 0.278 │ 0.274 │ 0.023 │ -0.259 │ 0.085 │ 0.304 │ 0.461 │ 0.796 │ 136.609 │ 131.956 │ 1.033 │ │ σ │ 10.007 │ 0.235 │ 0.015 │ 9.573 │ 9.852 │ 10.004 │ 10.163 │ 10.445 │ 259.157 │ 248.41 │ 1.009 │ └───┴────────┴───────┴────────┴────────┴───────┴────────┴────────┴────────┴──────────┴──────────┴───────┘ Constructing new sampler... Sampling starts... Computing... 0%|▏ | ETA: 0:01:47 ( 0.27 s/it) smc: diagnostics iter: 1000 Avgℓobjective: -1080.8711792073886 Temperature: 0.289050497374996 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.22777723263088684 generated: nothing generated_algorithm: nothing                   Computing... 36%|█████████ | ETA: 0:00:01 ( 4.59 ms/it) smc: diagnostics iter: 1035 Avgℓobjective: -3455.9346341294827 Temperature: 0.9241418199787566 ESS: 3.9998866650838414 resampled: true AvgJitterCorrelation: 0.1374984816847291 generated: nothing generated_algorithm: nothing                   Computing... 67%|████████████████▊ | ETA: 0:00:00 ( 2.87 ms/it) smc: diagnostics iter: 1066 Avgℓobjective: -3725.077337873807 Temperature: 0.9963157601005641 ESS: 3.999998728558011 resampled: true AvgJitterCorrelation: -0.049160456829724586 generated: nothing generated_algorithm: nothing                   Computing... 100%|█████████████████████████| Time: 0:00:00 ( 2.16 ms/it) smc: diagnostics iter: 1099 Avgℓobjective: -3737.9245738108393 Temperature: 0.9998636296729204 ESS: 3.9999999984462837 resampled: true AvgJitterCorrelation: 0.468115870511318 generated: nothing generated_algorithm: nothing Sampling finished, printing diagnostics and saving trace. ##################################################################################### SMC algorithm with jitter kernel MCMC Diagnostics: Sampler finished after 90 iterations with average acceptance ratio of 0.0%. Initial average ℓlikelihood per particle: -1870.003, variance: 4.061 Final average ℓlikelihood per particle: -3737.925, variance: 0.255 Total number of jittering steps: 117. Rejuvenations on average every 1.0 step, every 1.0 steps in first half, every 1.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.388, 0.145, 0.457, 0.652, 0.945]. Quantiles for average number rejuvenation steps: [1.0, 1.0, 1.0, 1.0, 3.775]. Quantiles for ESS: [3.976, 4.0, 4.0, 4.0, 4.0] for 4 chains. ┌───┬────────┬───────┬────────┬────────┬────────┬────────┬────────┬───────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼────────┼───────┼────────┼────────┼────────┼────────┼────────┼───────┼──────────┼──────────┼───────┤ │ μ │ 0.232 │ 0.345 │ 0.04 │ -0.411 │ -0.005 │ 0.213 │ 0.465 │ 0.926 │ 75.635 │ 95.695 │ 1.101 │ │ σ │ 10.005 │ 0.264 │ 0.016 │ 9.466 │ 9.837 │ 10.007 │ 10.191 │ 10.53 │ 253.704 │ 174.41 │ 1.034 │ └───┴────────┴───────┴────────┴────────┴────────┴────────┴────────┴───────┴──────────┴──────────┴───────┘ Sampling starts... Computing... 68%|█████████████████ | ETA: 0:00:00 ( 0.39 ms/it) smc: diagnostics iter: 1168 Avgℓobjective: -1556.518671511579 Temperature: 0.9969815836752917 ESS: 3.99999965138389 resampled: true AvgJitterCorrelation: 0.33160869463316783 generated: nothing generated_algorithm: nothing                   Computing... 100%|█████████████████████████| Time: 0:00:00 ( 0.65 ms/it) smc: diagnostics iter: 1199 Avgℓobjective: -1559.8999700721681 Temperature: 0.9998636296729204 ESS: 3.999999998963845 resampled: true AvgJitterCorrelation: 0.09199219205579551 generated: nothing generated_algorithm: nothing Sampling finished, printing diagnostics. ##################################################################################### SMC algorithm with jitter kernel MCMC Diagnostics: Sampler finished after 90 iterations with average acceptance ratio of 0.0%. Initial average ℓlikelihood per particle: -790.061, variance: 6.089 Final average ℓlikelihood per particle: -1559.9, variance: 1.671 Total number of jittering steps: 226. Rejuvenations on average every 1.0 step, every 1.0 steps in first half, every 1.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.419, 0.093, 0.396, 0.836, 1.0]. Quantiles for average number rejuvenation steps: [1.0, 1.0, 1.0, 2.0, 10.0]. Quantiles for ESS: [3.985, 4.0, 4.0, 4.0, 4.0] for 4 chains. ┌───┬────────┬───────┬────────┬────────┬────────┬────────┬────────┬───────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼────────┼───────┼────────┼────────┼────────┼────────┼────────┼───────┼──────────┼──────────┼───────┤ │ μ │ -0.026 │ 0.032 │ 0.002 │ -0.094 │ -0.048 │ -0.026 │ -0.005 │ 0.035 │ 176.094 │ 150.577 │ 1.037 │ │ σ │ 0.995 │ 0.03 │ 0.004 │ 0.942 │ 0.978 │ 0.994 │ 1.013 │ 1.056 │ 62.166 │ 45.068 │ 1.048 │ └───┴────────┴───────┴────────┴────────┴────────┴────────┴────────┴───────┴──────────┴──────────┴───────┘ Constructing new sampler... Sampling starts... Computing... 0%| | ETA: 0:08:02 ( 0.60 s/it) smc: diagnostics iter: 1000 Avgℓobjective: -13600.871606312277 Temperature: 0.289050497374996 ESS: 4.0 resampled: true AvgJitterCorrelation: NaN generated: nothing generated_algorithm: nothing                   Computing... 13%|███▎ | ETA: 0:00:14 (19.76 ms/it) smc: diagnostics iter: 1050 Avgℓobjective: -3671.045391841777 Temperature: 0.9820137900379085 ESS: 3.999995669554592 resampled: true AvgJitterCorrelation: 0.5195366486250343 generated: nothing generated_algorithm: nothing                   Computing... 24%|██████▏ | ETA: 0:00:08 (12.75 ms/it) smc: diagnostics iter: 1097 Avgℓobjective: -3737.6125041447194 Temperature: 0.9998334419352227 ESS: 3.9999999999587743 resampled: true AvgJitterCorrelation: 0.8109206334756265 generated: nothing generated_algorithm: nothing                   Computing... 32%|████████ | ETA: 0:00:06 (11.81 ms/it) smc: diagnostics iter: 1026 Avgℓobjective: -3110.1368251515805 Temperature: 0.8320183851339245 ESS: 3.9994090323239515 resampled: true AvgJitterCorrelation: 0.6980206428348388 generated: nothing generated_algorithm: nothing                   Computing... 33%|████████▎ | ETA: 0:00:07 (12.52 ms/it) smc: diagnostics iter: 1032 Avgℓobjective: -3366.8153813157155 Temperature: 0.9002495108803148 ESS: 3.9994573941103964 resampled: true AvgJitterCorrelation: 0.9116271858961864 generated: nothing generated_algorithm: nothing                   Computing... 34%|████████▌ | ETA: 0:00:07 (12.83 ms/it) smc: diagnostics iter: 1034 Avgℓobjective: -3429.096551083705 Temperature: 0.9168273035060777 ESS: 3.999391299156135 resampled: true AvgJitterCorrelation: 0.2935439341016699 generated: nothing generated_algorithm: nothing                   Computing... 34%|████████▌ | ETA: 0:00:07 (13.22 ms/it) smc: diagnostics iter: 1036 Avgℓobjective: -3480.352200381028 Temperature: 0.9308615796566533 ESS: 3.999471622241108 resampled: true AvgJitterCorrelation: 0.5347798667043848 generated: nothing generated_algorithm: nothing                   Computing... 35%|████████▊ | ETA: 0:00:07 (13.66 ms/it) mcmc: diagnostics iter: 41 logobjective: -3560.7756624209246 Temperature: 0.9525741268224334 accepted: true acceptancerate: 1.5287829938486601e-140 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 2 ℓH: -3561.261538161549                         Computing... 36%|████████▉ | ETA: 0:00:07 (14.07 ms/it) smc: diagnostics iter: 1041 Avgℓobjective: -3578.472569670824 Temperature: 0.9568927450589139 ESS: 3.999968218755176 resampled: true AvgJitterCorrelation: -0.23979508124274393 generated: nothing generated_algorithm: nothing                   Computing... 36%|█████████ | ETA: 0:00:07 (14.48 ms/it) smc: diagnostics iter: 1043 Avgℓobjective: -3606.6694260235695 Temperature: 0.9644288107273639 ESS: 3.99968190105348 resampled: true AvgJitterCorrelation: 0.8147048702358595 generated: nothing generated_algorithm: nothing                   Computing... 44%|██████████▉ | ETA: 0:00:06 (12.50 ms/it) mcmc: diagnostics iter: 75 logobjective: -3731.95771266455 Temperature: 0.9983411989198255 accepted: true acceptancerate: 3.4453466954259286e-60 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 3 ℓH: -3732.019265511272                         Computing... 48%|███████████▉ | ETA: 0:00:05 (11.90 ms/it) mcmc: diagnostics iter: 91 logobjective: -3735.523452735309 Temperature: 0.9996646498695336 accepted: true acceptancerate: 1.6419257189624952e-13 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 3 ℓH: -3736.073018271101                         Computing... 50%|████████████▌ | ETA: 0:00:05 (11.60 ms/it) smc: diagnostics iter: 1099 Avgℓobjective: -3738.419742604121 Temperature: 0.9998636296729204 ESS: 3.999999998254319 resampled: true AvgJitterCorrelation: 0.4937600385326119 generated: nothing generated_algorithm: nothing                   Computing... 66%|████████████████▌ | ETA: 0:00:03 (12.43 ms/it) smc: diagnostics iter: 1063 Avgℓobjective: -3720.476421609128 Temperature: 0.995033198349943 ESS: 3.9999992182325323 resampled: true AvgJitterCorrelation: 0.779378405894294 generated: nothing generated_algorithm: nothing                   Computing... 71%|█████████████████▋ | ETA: 0:00:03 (11.92 ms/it) mcmc: diagnostics iter: 83 logobjective: -3735.8442707053896 Temperature: 0.9992539711661633 accepted: true acceptancerate: 0.019968894646753967 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 3 ℓH: -3737.7277605820977                         Computing... 73%|██████████████████▍ | ETA: 0:00:02 (11.65 ms/it) mcmc: diagnostics iter: 94 logobjective: -3736.350325502636 Temperature: 0.9997515449181605 accepted: true acceptancerate: 0.0077649901375540465 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 3 ℓH: -3736.8840357969716                         Computing... 80%|████████████████████ | ETA: 0:00:02 (10.89 ms/it) smc: diagnostics iter: 1018 Avgℓobjective: -2711.61644685012 Temperature: 0.6899744811276125 ESS: 3.7296405716388064 resampled: true AvgJitterCorrelation: 0.8678232342085621 generated: nothing generated_algorithm: nothing                   Computing... 86%|█████████████████████▌ | ETA: 0:00:01 (11.63 ms/it) smc: diagnostics iter: 1042 Avgℓobjective: -3591.425362465653 Temperature: 0.9608342772032357 ESS: 3.999957880053917 resampled: true AvgJitterCorrelation: 0.2757605046368099 generated: nothing generated_algorithm: nothing                   Computing... 86%|█████████████████████▋ | ETA: 0:00:01 (11.75 ms/it) mcmc: diagnostics iter: 46 logobjective: -3625.9905964709064 Temperature: 0.9706877692486436 accepted: true acceptancerate: 1.3469019682177533e-12 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 2 ℓH: -3626.09756497255                         Computing... 87%|█████████████████████▊ | ETA: 0:00:01 (11.86 ms/it) mcmc: diagnostics iter: 48 logobjective: -3645.390071789116 Temperature: 0.9758729785823308 accepted: true acceptancerate: 3.21535455257507e-7 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 2 ℓH: -3645.919145167968                         Computing... 88%|█████████████████████▉ | ETA: 0:00:01 (11.93 ms/it) smc: diagnostics iter: 1049 Avgℓobjective: -3664.764647712944 Temperature: 0.9801596942659225 ESS: 3.999983648909917 resampled: true AvgJitterCorrelation: 0.30109765992907095 generated: nothing generated_algorithm: nothing                   Computing... 91%|██████████████████████▊ | ETA: 0:00:01 (11.63 ms/it) smc: diagnostics iter: 1064 Avgℓobjective: -3721.861382721311 Temperature: 0.9955037268390589 ESS: 3.999998521329442 resampled: true AvgJitterCorrelation: 0.8247230666172161 generated: nothing generated_algorithm: nothing                   Computing... 94%|███████████████████████▌ | ETA: 0:00:01 (11.48 ms/it) smc: diagnostics iter: 1075 Avgℓobjective: -3733.0430767824137 Temperature: 0.998498817743263 ESS: 3.999999973328187 resampled: true AvgJitterCorrelation: -0.033726065342165046 generated: nothing generated_algorithm: nothing                   Computing... 96%|████████████████████████▏| ETA: 0:00:00 (11.32 ms/it) smc: diagnostics iter: 1085 Avgℓobjective: -3736.5200400304407 Temperature: 0.9994472213630764 ESS: 3.999999987715121 resampled: true AvgJitterCorrelation: 0.7740881463314857 generated: nothing generated_algorithm: nothing                   Computing... 99%|████████████████████████▊| ETA: 0:00:00 (11.19 ms/it) smc: diagnostics iter: 1095 Avgℓobjective: -3738.1739272827635 Temperature: 0.9997965730219448 ESS: 3.9999999967169613 resampled: true AvgJitterCorrelation: 0.5971625760643517 generated: nothing generated_algorithm: nothing                   Computing... 100%|█████████████████████████| Time: 0:00:08 (11.17 ms/it) smc: diagnostics iter: 1099 Avgℓobjective: -3737.9856827315293 Temperature: 0.9998636296729204 ESS: 3.999999999443175 resampled: true AvgJitterCorrelation: 0.9089155567285022 generated: nothing generated_algorithm: nothing Sampling finished, printing diagnostics and saving trace. ##################################################################################### ########################################## Chain 1: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -4098.395, Avg. final ℓposterior: -3735.223. NUTS sampler had 53 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 1.556 (3) number of steps and depth of 0.711 (1). Divergences in: Warmup: 47, Adaptionˢˡᵒʷ: 6, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 2: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -4240.235, Avg. final ℓposterior: -3738.397. NUTS sampler had 51 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 1.767 (3) number of steps and depth of 0.833 (1). Divergences in: Warmup: 42, Adaptionˢˡᵒʷ: 9, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 3: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -2092.83, Avg. final ℓposterior: -3734.939. NUTS sampler had 47 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 1.833 (1) number of steps and depth of 0.878 (1). Divergences in: Warmup: 43, Adaptionˢˡᵒʷ: 4, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 4: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -8745.287, Avg. final ℓposterior: -3735.284. NUTS sampler had 47 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 1.556 (3) number of steps and depth of 0.811 (1). Divergences in: Warmup: 42, Adaptionˢˡᵒʷ: 5, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ##################################################################################### ########################################## Chain 1: SMC Diagnostics: SMC algorithm with jitter kernel MCMC Diagnostics: Sampler finished after 90 iterations with average acceptance ratio of 0.0%. Initial average ℓlikelihood per particle: -4093.29, variance: 30.459 Final average ℓlikelihood per particle: -3737.716, variance: 0.145 Total number of jittering steps: 192. Rejuvenations on average every 1.0 step, every 1.0 steps in first half, every 1.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.564, 0.145, 0.454, 0.799, 0.946]. Quantiles for average number rejuvenation steps: [1.0, 1.0, 1.0, 2.0, 10.0]. Quantiles for ESS: [1.0, 3.806, 4.0, 4.0, 4.0] for 4 chains. ########################################## Chain 2: SMC Diagnostics: SMC algorithm with jitter kernel MCMC Diagnostics: Sampler finished after 90 iterations with average acceptance ratio of 0.0%. Initial average ℓlikelihood per particle: -4081.176, variance: 83709.878 Final average ℓlikelihood per particle: -3738.42, variance: 2.191 Total number of jittering steps: 195. Rejuvenations on average every 1.0 step, every 1.0 steps in first half, every 1.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.407, 0.011, 0.39, 0.676, 0.943]. Quantiles for average number rejuvenation steps: [1.0, 1.0, 1.0, 1.75, 10.0]. Quantiles for ESS: [1.25, 4.0, 4.0, 4.0, 4.0] for 4 chains. ########################################## Chain 3: SMC Diagnostics: SMC algorithm with jitter kernel MCMC Diagnostics: Sampler finished after 90 iterations with average acceptance ratio of 0.0%. Initial average ℓlikelihood per particle: -2087.519, variance: 29.908 Final average ℓlikelihood per particle: -3738.09, variance: 0.823 Total number of jittering steps: 196. Rejuvenations on average every 1.0 step, every 1.0 steps in first half, every 1.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.523, 0.148, 0.437, 0.669, 0.959]. Quantiles for average number rejuvenation steps: [1.0, 1.0, 1.0, 2.0, 10.0]. Quantiles for ESS: [2.546, 4.0, 4.0, 4.0, 4.0] for 4 chains. ########################################## Chain 4: SMC Diagnostics: SMC algorithm with jitter kernel MCMC Diagnostics: Sampler finished after 90 iterations with average acceptance ratio of 0.0%. Initial average ℓlikelihood per particle: -8093.206, variance: 1.017982357e6 Final average ℓlikelihood per particle: -3737.986, variance: 0.382 Total number of jittering steps: 195. Rejuvenations on average every 1.0 step, every 1.0 steps in first half, every 1.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.511, 0.057, 0.568, 0.823, 0.97]. Quantiles for average number rejuvenation steps: [1.0, 1.0, 1.0, 1.0, 10.0]. Quantiles for ESS: [1.0, 4.0, 4.0, 4.0, 4.0] for 4 chains. ┌───┬───────┬───────┬────────┬────────┬────────┬───────┬────────┬────────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼───────┼───────┼────────┼────────┼────────┼───────┼────────┼────────┼──────────┼──────────┼───────┤ │ μ │ 0.201 │ 0.308 │ 0.024 │ -0.345 │ -0.006 │ 0.153 │ 0.419 │ 0.817 │ 159.234 │ 161.926 │ 1.035 │ │ σ │ 9.508 │ 1.911 │ 0.471 │ 3.412 │ 9.765 │ 9.975 │ 10.151 │ 10.624 │ 37.747 │ 28.469 │ 1.083 │ └───┴───────┴───────┴────────┴────────┴────────┴───────┴────────┴────────┴──────────┴──────────┴───────┘ Sampling starts... Computing... 0%| | ETA: 0:04:09 ( 0.31 s/it) smc: diagnostics iter: 1100 Avgℓobjective: -937.7688287835126 Temperature: 0.289050497374996 ESS: 3.999999999910658 resampled: true AvgJitterCorrelation: 0.43461781368192964 generated: nothing generated_algorithm: nothing                   Computing... 9%|██▎ | ETA: 0:00:07 (10.00 ms/it) smc: diagnostics iter: 1136 Avgℓobjective: -1466.6280737497952 Temperature: 0.9308615796566533 ESS: 3.9999042939119716 resampled: true AvgJitterCorrelation: -0.03281446260683235 generated: nothing generated_algorithm: nothing                   Computing... 17%|████▍ | ETA: 0:00:04 ( 6.18 ms/it) mcmc: diagnostics iter: 170 logobjective: -1569.884747881972 Temperature: 0.997268039236989 accepted: true acceptancerate: 0.0001405088220695125 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 1 ℓH: -1570.9525413508973                         Computing... 25%|██████▎ | ETA: 0:00:03 ( 4.77 ms/it) smc: diagnostics iter: 1100 Avgℓobjective: -958.4929034982384 Temperature: 0.289050497374996 ESS: 3.999999998647864 resampled: true AvgJitterCorrelation: 0.7612837680514342 generated: nothing generated_algorithm: nothing                   Computing... 33%|████████▎ | ETA: 0:00:02 ( 4.03 ms/it) mcmc: diagnostics iter: 133 logobjective: -1417.2228321166197 Temperature: 0.9002495108803148 accepted: true acceptancerate: 2.7897576143166795e-24 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 2 ℓH: -1417.3626850474989                         Computing... 42%|██████████▌ | ETA: 0:00:02 ( 3.47 ms/it) smc: diagnostics iter: 1168 Avgℓobjective: -1570.0142208582736 Temperature: 0.9969815836752917 ESS: 3.999999432596185 resampled: true AvgJitterCorrelation: 0.3713510464128573 generated: nothing generated_algorithm: nothing                   Computing... 52%|█████████████ | ETA: 0:00:01 ( 3.05 ms/it) mcmc: diagnostics iter: 109 logobjective: -829.783119415147 Temperature: 0.45016600268752216 accepted: true acceptancerate: 4.4685276823992674e-42 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 1 ℓH: -830.3128224772126                         Computing... 62%|███████████████▌ | ETA: 0:00:01 ( 2.83 ms/it) smc: diagnostics iter: 1147 Avgℓobjective: -1536.6034084174325 Temperature: 0.9758729785823308 ESS: 3.999994938135255 resampled: true AvgJitterCorrelation: -0.5691780527800511 generated: nothing generated_algorithm: nothing                   Computing... 72%|██████████████████ | ETA: 0:00:01 ( 2.61 ms/it) smc: diagnostics iter: 1188 Avgℓobjective: -1574.205838717476 Temperature: 0.9995904328350139 ESS: 3.999999999232921 resampled: true AvgJitterCorrelation: 0.635025767486175 generated: nothing generated_algorithm: nothing                   Computing... 82%|████████████████████▋ | ETA: 0:00:00 ( 2.53 ms/it) mcmc: diagnostics iter: 130 logobjective: -1371.7528665412458 Temperature: 0.8698915256370021 accepted: true acceptancerate: 0.0 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 1 ℓH: -1372.5023337534542                         Computing... 89%|██████████████████████▎ | ETA: 0:00:00 ( 2.50 ms/it) smc: diagnostics iter: 1155 Avgℓobjective: -1557.1436505933295 Temperature: 0.9890130573694068 ESS: 3.999990519835789 resampled: true AvgJitterCorrelation: 0.05447017186986412 generated: nothing generated_algorithm: nothing                   Computing... 96%|████████████████████████ | ETA: 0:00:00 ( 2.45 ms/it) smc: diagnostics iter: 1183 Avgℓobjective: -1573.3910445244442 Temperature: 0.9993249172693672 ESS: 3.9999999903166232 resampled: true AvgJitterCorrelation: 0.6966612626570061 generated: nothing generated_algorithm: nothing                   Computing... 100%|█████████████████████████| Time: 0:00:01 ( 2.41 ms/it) smc: diagnostics iter: 1199 Avgℓobjective: -1574.1110214434111 Temperature: 0.9998636296729204 ESS: 3.9999999999258415 resampled: true AvgJitterCorrelation: 0.9054270495970107 generated: nothing generated_algorithm: nothing Sampling finished, printing diagnostics. ##################################################################################### ########################################## Chain 1: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -903.438, Avg. final ℓposterior: -1576.357. NUTS sampler had 45 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 1.689 (1) number of steps and depth of 0.9 (1). Divergences in: Warmup: 39, Adaptionˢˡᵒʷ: 6, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 2: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -928.707, Avg. final ℓposterior: -1575.285. NUTS sampler had 31 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 1.578 (1) number of steps and depth of 0.978 (1). Divergences in: Warmup: 25, Adaptionˢˡᵒʷ: 6, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 3: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -831.649, Avg. final ℓposterior: -1574.154. NUTS sampler had 49 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 1.611 (1) number of steps and depth of 0.822 (1). Divergences in: Warmup: 37, Adaptionˢˡᵒʷ: 12, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 4: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -788.049, Avg. final ℓposterior: -1574.505. NUTS sampler had 43 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 1.656 (1) number of steps and depth of 0.9 (1). Divergences in: Warmup: 32, Adaptionˢˡᵒʷ: 11, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ##################################################################################### ########################################## Chain 1: SMC Diagnostics: SMC algorithm with jitter kernel MCMC Diagnostics: Sampler finished after 90 iterations with average acceptance ratio of 0.0%. Initial average ℓlikelihood per particle: -1057.073, variance: 34.626 Final average ℓlikelihood per particle: -1574.757, variance: 1.356 Total number of jittering steps: 125. Rejuvenations on average every 1.0 step, every 1.0 steps in first half, every 1.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.567, 0.069, 0.419, 0.728, 0.974]. Quantiles for average number rejuvenation steps: [1.0, 1.0, 1.0, 1.0, 6.55]. Quantiles for ESS: [2.386, 4.0, 4.0, 4.0, 4.0] for 4 chains. ########################################## Chain 2: SMC Diagnostics: SMC algorithm with jitter kernel MCMC Diagnostics: Sampler finished after 90 iterations with average acceptance ratio of 0.0%. Initial average ℓlikelihood per particle: -879.491, variance: 1122.932 Final average ℓlikelihood per particle: -1574.932, variance: 1.423 Total number of jittering steps: 186. Rejuvenations on average every 1.0 step, every 1.0 steps in first half, every 1.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.542, 0.185, 0.614, 0.857, 0.992]. Quantiles for average number rejuvenation steps: [1.0, 1.0, 1.0, 1.0, 10.0]. Quantiles for ESS: [2.967, 4.0, 4.0, 4.0, 4.0] for 4 chains. ########################################## Chain 3: SMC Diagnostics: SMC algorithm with jitter kernel MCMC Diagnostics: Sampler finished after 90 iterations with average acceptance ratio of 0.0%. Initial average ℓlikelihood per particle: -826.988, variance: 136.81 Final average ℓlikelihood per particle: -1574.63, variance: 0.22 Total number of jittering steps: 229. Rejuvenations on average every 1.0 step, every 1.0 steps in first half, every 1.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.753, 0.13, 0.587, 0.83, 1.0]. Quantiles for average number rejuvenation steps: [1.0, 1.0, 1.0, 2.0, 10.0]. Quantiles for ESS: [2.972, 4.0, 4.0, 4.0, 4.0] for 4 chains. ########################################## Chain 4: SMC Diagnostics: SMC algorithm with jitter kernel MCMC Diagnostics: Sampler finished after 90 iterations with average acceptance ratio of 0.0%. Initial average ℓlikelihood per particle: -788.497, variance: 1.092 Final average ℓlikelihood per particle: -1574.111, variance: 0.102 Total number of jittering steps: 150. Rejuvenations on average every 1.0 step, every 1.0 steps in first half, every 1.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.545, 0.034, 0.366, 0.702, 0.979]. Quantiles for average number rejuvenation steps: [1.0, 1.0, 1.0, 1.0, 10.0]. Quantiles for ESS: [3.992, 4.0, 4.0, 4.0, 4.0] for 4 chains. ┌───┬───────┬───────┬────────┬────────┬───────┬───────┬───────┬───────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼───────┼───────┼────────┼────────┼───────┼───────┼───────┼───────┼──────────┼──────────┼───────┤ │ μ │ 0.031 │ 0.048 │ 0.003 │ -0.045 │ 0.006 │ 0.029 │ 0.049 │ 0.105 │ 321.709 │ 170.957 │ 1.007 │ │ σ │ 1.029 │ 0.124 │ 0.015 │ 0.969 │ 0.998 │ 1.014 │ 1.028 │ 1.185 │ 102.189 │ 44.807 │ 1.034 │ └───┴───────┴───────┴────────┴────────┴───────┴───────┴───────┴───────┴──────────┴──────────┴───────┘ Constructing new sampler... Sampling starts... Computing... 0%|▏ | ETA: 0:03:16 ( 0.49 s/it) mcmc: diagnostics iter: 1 logobjective: -1867.8799667514077 Temperature: 0.5 accepted: true acceptancerate: 0.8663145909811866 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 1 ℓH: -1867.8941454291996                         Computing... 100%|█████████████████████████| Time: 0:00:01 ( 2.92 ms/it) mcmc: diagnostics iter: 100 logobjective: -1868.7028090586434 Temperature: 0.5 accepted: true acceptancerate: 0.9999607625955212 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 15 ℓH: -1869.0950799838947 Sampling finished, printing diagnostics and saving trace. ##################################################################################### ########################################## Chain 1: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1867.993, Avg. final ℓposterior: -1868.032. NUTS sampler had 22 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 12.067 (47) number of steps and depth of 2.0 (5). Divergences in: Warmup: 22, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 2: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1867.954, Avg. final ℓposterior: -1867.938. NUTS sampler had 22 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 11.633 (47) number of steps and depth of 1.956 (5). Divergences in: Warmup: 22, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 3: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1868.704, Avg. final ℓposterior: -1868.629. NUTS sampler had 20 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 26.056 (7) number of steps and depth of 2.256 (3). Divergences in: Warmup: 20, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 4: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1868.325, Avg. final ℓposterior: -1868.703. NUTS sampler had 18 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 10.844 (15) number of steps and depth of 2.0 (3). Divergences in: Warmup: 18, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ┌───┬────────┬───────┬────────┬───────┬────────┬────────┬───────┬────────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼────────┼───────┼────────┼───────┼────────┼────────┼───────┼────────┼──────────┼──────────┼───────┤ │ μ │ 0.134 │ 0.294 │ 0.092 │ -0.49 │ -0.055 │ 0.09 │ 0.362 │ 0.634 │ 10.454 │ 36.397 │ 1.38 │ │ σ │ 10.058 │ 0.257 │ 0.03 │ 9.566 │ 9.86 │ 10.002 │ 10.28 │ 10.474 │ 77.03 │ 173.527 │ 1.081 │ └───┴────────┴───────┴────────┴───────┴────────┴────────┴───────┴────────┴──────────┴──────────┴───────┘ Sampling starts... Computing... 0%|▏ | ETA: 0:01:34 ( 0.24 s/it) mcmc: diagnostics iter: 101 logobjective: -1868.569334030872 Temperature: 0.5 accepted: true acceptancerate: 0.9986108298657382 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 31 ℓH: -1869.5546481329868                         Computing... 22%|█████▌ | ETA: 0:00:02 ( 6.43 ms/it) mcmc: diagnostics iter: 123 logobjective: -1869.1587090978996 Temperature: 0.5 accepted: true acceptancerate: 0.9999694634383884 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 31 ℓH: -1870.7643224640633                         Computing... 55%|█████████████▊ | ETA: 0:00:01 ( 3.07 ms/it) mcmc: diagnostics iter: 155 logobjective: -1868.54866414796 Temperature: 0.5 accepted: true acceptancerate: 0.9952982316845713 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 31 ℓH: -1869.8724436390153                         Computing... 92%|██████████████████████▉ | ETA: 0:00:00 ( 2.12 ms/it) mcmc: diagnostics iter: 192 logobjective: -1867.796152304745 Temperature: 0.5 accepted: true acceptancerate: 0.9998543465428406 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 39 ℓH: -1868.1921327962327                         Computing... 100%|█████████████████████████| Time: 0:00:00 ( 2.00 ms/it) mcmc: diagnostics iter: 200 logobjective: -1867.7840185398718 Temperature: 0.5 accepted: true acceptancerate: 0.9994690389044901 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 15 ℓH: -1868.74836988976 Sampling finished, printing diagnostics. ##################################################################################### ########################################## Chain 1: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1868.856, Avg. final ℓposterior: -1868.143. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 18.6 (15) number of steps and depth of 3.622 (3). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 2: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1868.474, Avg. final ℓposterior: -1868.244. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 29.756 (31) number of steps and depth of 4.311 (4). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 3: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1869.062, Avg. final ℓposterior: -1867.972. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 25.244 (15) number of steps and depth of 4.056 (4). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 4: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1867.788, Avg. final ℓposterior: -1867.784. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 20.4 (15) number of steps and depth of 3.644 (4). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ┌───┬────────┬───────┬────────┬────────┬────────┬────────┬────────┬────────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼────────┼───────┼────────┼────────┼────────┼────────┼────────┼────────┼──────────┼──────────┼───────┤ │ μ │ 0.262 │ 0.497 │ 0.056 │ -0.772 │ -0.093 │ 0.268 │ 0.595 │ 1.206 │ 76.912 │ 96.764 │ 1.048 │ │ σ │ 10.045 │ 0.305 │ 0.019 │ 9.518 │ 9.828 │ 10.024 │ 10.251 │ 10.641 │ 255.421 │ 272.288 │ 1.008 │ └───┴────────┴───────┴────────┴────────┴────────┴────────┴────────┴────────┴──────────┴──────────┴───────┘ Constructing new sampler... Sampling starts... Computing... 0%|▏ | ETA: 0:01:52 ( 0.28 s/it) smc: diagnostics iter: 1000 Avgℓobjective: -1869.2856463891535 Temperature: 0.5 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.9823001420538695 generated: nothing generated_algorithm: nothing                   Computing... 26%|██████▍ | ETA: 0:00:02 ( 7.06 ms/it) smc: diagnostics iter: 1025 Avgℓobjective: -1869.9891399739683 Temperature: 0.5 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.32584611095413935 generated: nothing generated_algorithm: nothing                   Computing... 42%|██████████▌ | ETA: 0:00:01 ( 5.11 ms/it) smc: diagnostics iter: 1041 Avgℓobjective: -1869.950802286566 Temperature: 0.5 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.44952870653649785 generated: nothing generated_algorithm: nothing                   Computing... 57%|██████████████▎ | ETA: 0:00:01 ( 4.20 ms/it) smc: diagnostics iter: 1057 Avgℓobjective: -1869.6602011676855 Temperature: 0.5 ESS: 4.0 resampled: true AvgJitterCorrelation: -0.5604442791782143 generated: nothing generated_algorithm: nothing                   Computing... 91%|██████████████████████▊ | ETA: 0:00:00 ( 2.92 ms/it) smc: diagnostics iter: 1091 Avgℓobjective: -1871.7903360589128 Temperature: 0.5 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.6914736077470676 generated: nothing generated_algorithm: nothing                   Computing... 100%|█████████████████████████| Time: 0:00:01 ( 2.73 ms/it) smc: diagnostics iter: 1099 Avgℓobjective: -1869.9486230551076 Temperature: 0.5 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.6034591689537387 generated: nothing generated_algorithm: nothing Sampling finished, printing diagnostics and saving trace. ##################################################################################### SMC algorithm with jitter kernel MCMC Diagnostics: Sampler finished after 90 iterations with average acceptance ratio of 0.0%. Initial average ℓlikelihood per particle: -1869.732, variance: 1.325 Final average ℓlikelihood per particle: -1869.949, variance: 1.401 Total number of jittering steps: 117. Rejuvenations on average every 1.0 step, every 1.0 steps in first half, every 1.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.418, 0.076, 0.322, 0.684, 0.928]. Quantiles for average number rejuvenation steps: [1.0, 1.0, 1.0, 1.0, 3.0]. Quantiles for ESS: [4.0, 4.0, 4.0, 4.0, 4.0] for 4 chains. ┌───┬────────┬───────┬────────┬────────┬───────┬────────┬────────┬────────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼────────┼───────┼────────┼────────┼───────┼────────┼────────┼────────┼──────────┼──────────┼───────┤ │ μ │ 0.243 │ 0.422 │ 0.044 │ -0.583 │ -0.06 │ 0.252 │ 0.559 │ 1.046 │ 94.139 │ 129.864 │ 1.014 │ │ σ │ 10.037 │ 0.34 │ 0.022 │ 9.4 │ 9.796 │ 10.038 │ 10.279 │ 10.655 │ 242.661 │ 189.737 │ 1.017 │ └───┴────────┴───────┴────────┴────────┴───────┴────────┴────────┴────────┴──────────┴──────────┴───────┘ Sampling starts... Computing... 68%|█████████████████ | ETA: 0:00:00 ( 0.38 ms/it) smc: diagnostics iter: 1167 Avgℓobjective: -787.1973799585855 Temperature: 0.5 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.6753292606938317 generated: nothing generated_algorithm: nothing                   Computing... 100%|█████████████████████████| Time: 0:00:00 ( 0.65 ms/it) smc: diagnostics iter: 1199 Avgℓobjective: -788.5307634639648 Temperature: 0.5 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.8083091362250122 generated: nothing generated_algorithm: nothing Sampling finished, printing diagnostics. ##################################################################################### SMC algorithm with jitter kernel MCMC Diagnostics: Sampler finished after 90 iterations with average acceptance ratio of 0.0%. Initial average ℓlikelihood per particle: -788.155, variance: 0.857 Final average ℓlikelihood per particle: -788.531, variance: 1.558 Total number of jittering steps: 201. Rejuvenations on average every 1.0 step, every 1.0 steps in first half, every 1.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.067, 0.332, 0.625, 0.838, 0.959]. Quantiles for average number rejuvenation steps: [1.0, 1.0, 1.0, 3.0, 7.0]. Quantiles for ESS: [4.0, 4.0, 4.0, 4.0, 4.0] for 4 chains. ┌───┬───────┬───────┬────────┬────────┬────────┬───────┬───────┬───────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼───────┼───────┼────────┼────────┼────────┼───────┼───────┼───────┼──────────┼──────────┼───────┤ │ μ │ 0.017 │ 0.048 │ 0.005 │ -0.076 │ -0.015 │ 0.014 │ 0.053 │ 0.107 │ 95.393 │ 74.252 │ 1.024 │ │ σ │ 1.014 │ 0.028 │ 0.003 │ 0.97 │ 0.993 │ 1.011 │ 1.033 │ 1.075 │ 116.915 │ 82.666 │ 1.019 │ └───┴───────┴───────┴────────┴────────┴────────┴───────┴───────┴───────┴──────────┴──────────┴───────┘ Constructing new sampler... Sampling starts... Computing... 0%| | ETA: 0:08:37 ( 0.65 s/it) smc: diagnostics iter: 1000 Avgℓobjective: -22973.66692718849 Temperature: 0.5 ESS: 4.0 resampled: true AvgJitterCorrelation: NaN generated: nothing generated_algorithm: nothing                   Computing... 13%|███▎ | ETA: 0:00:10 (13.71 ms/it) smc: diagnostics iter: 1012 Avgℓobjective: -5168.1376392879065 Temperature: 0.5 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.8788613764867206 generated: nothing generated_algorithm: nothing                   Computing... 25%|██████▎ | ETA: 0:00:11 (19.13 ms/it) smc: diagnostics iter: 1024 Avgℓobjective: -1871.2281856197565 Temperature: 0.5 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.09709702065402553 generated: nothing generated_algorithm: nothing                   Computing... 26%|██████▌ | ETA: 0:00:11 (18.88 ms/it) mcmc: diagnostics iter: 27 logobjective: -1867.731605995684 Temperature: 0.5 accepted: true acceptancerate: 0.005603175034164652 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 3 ℓH: -1868.8806512182841                         Computing... 27%|██████▊ | ETA: 0:00:11 (18.71 ms/it) mcmc: diagnostics iter: 28 logobjective: -1867.7382664723398 Temperature: 0.5 accepted: true acceptancerate: 4.587479230108683e-23 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 1 ℓH: -1869.6247433431063                         Computing... 29%|███████▎ | ETA: 0:00:10 (17.93 ms/it) mcmc: diagnostics iter: 30 logobjective: -1868.466443395538 Temperature: 0.5 accepted: true acceptancerate: 0.16730444359697708 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 3 ℓH: -1869.0712962994457                         Computing... 31%|███████▊ | ETA: 0:00:10 (17.79 ms/it) mcmc: diagnostics iter: 31 logobjective: -1868.3782289435758 Temperature: 0.5 accepted: true acceptancerate: 2.506185943108729e-67 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 1 ℓH: -1869.3859920420457                         Computing... 33%|████████▎ | ETA: 0:00:09 (17.13 ms/it) smc: diagnostics iter: 1032 Avgℓobjective: -1869.1554871003123 Temperature: 0.5 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.32809425347681104 generated: nothing generated_algorithm: nothing                   Computing... 35%|████████▋ | ETA: 0:00:09 (16.88 ms/it) mcmc: diagnostics iter: 35 logobjective: -2411.3519868759167 Temperature: 0.5 accepted: true acceptancerate: 0.0 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 1 ℓH: -2411.8480912046807                         Computing... 36%|█████████ | ETA: 0:00:09 (16.99 ms/it) smc: diagnostics iter: 1035 Avgℓobjective: -1965.3775608333704 Temperature: 0.5 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.23549265980260425 generated: nothing generated_algorithm: nothing                   Computing... 40%|██████████▏ | ETA: 0:00:07 (15.70 ms/it) mcmc: diagnostics iter: 41 logobjective: -1867.7129104588432 Temperature: 0.5 accepted: true acceptancerate: 0.035804334583383314 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 3 ℓH: -1868.5749993615152                         Computing... 43%|██████████▊ | ETA: 0:00:07 (15.20 ms/it) smc: diagnostics iter: 1042 Avgℓobjective: -1888.3727363273872 Temperature: 0.5 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.8847253652597155 generated: nothing generated_algorithm: nothing                   Computing... 45%|███████████▎ | ETA: 0:00:06 (14.72 ms/it) smc: diagnostics iter: 1044 Avgℓobjective: -1870.3050188662462 Temperature: 0.5 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.09975347837670212 generated: nothing generated_algorithm: nothing                   Computing... 48%|███████████▉ | ETA: 0:00:06 (14.24 ms/it) smc: diagnostics iter: 1047 Avgℓobjective: -1870.12125912789 Temperature: 0.5 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.4972632721165929 generated: nothing generated_algorithm: nothing                   Computing... 50%|████████████▌ | ETA: 0:00:06 (13.78 ms/it) smc: diagnostics iter: 1049 Avgℓobjective: -1869.1898412517633 Temperature: 0.5 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.2492331470475288 generated: nothing generated_algorithm: nothing                   Computing... 52%|█████████████▏ | ETA: 0:00:05 (13.37 ms/it) smc: diagnostics iter: 1052 Avgℓobjective: -1869.8647761349553 Temperature: 0.5 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.24549334102433953 generated: nothing generated_algorithm: nothing                   Computing... 55%|█████████████▊ | ETA: 0:00:05 (13.05 ms/it) mcmc: diagnostics iter: 55 logobjective: -1869.7076007211797 Temperature: 0.5 accepted: true acceptancerate: 2.30304797763925e-44 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 2 ℓH: -1870.0620808557621                         Computing... 57%|██████████████▎ | ETA: 0:00:04 (12.83 ms/it) smc: diagnostics iter: 1056 Avgℓobjective: -1869.527175740438 Temperature: 0.5 ESS: 4.0 resampled: true AvgJitterCorrelation: -0.07386930253720769 generated: nothing generated_algorithm: nothing                   Computing... 59%|██████████████▊ | ETA: 0:00:04 (12.72 ms/it) smc: diagnostics iter: 1058 Avgℓobjective: -1870.0045139087051 Temperature: 0.5 ESS: 4.0 resampled: true AvgJitterCorrelation: -0.03870441313464429 generated: nothing generated_algorithm: nothing                   Computing... 60%|███████████████ | ETA: 0:00:04 (12.62 ms/it) smc: diagnostics iter: 1060 Avgℓobjective: -1869.1829839403938 Temperature: 0.5 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.038585454050751145 generated: nothing generated_algorithm: nothing                   Computing... 63%|███████████████▊ | ETA: 0:00:04 (12.27 ms/it) smc: diagnostics iter: 1062 Avgℓobjective: -1869.4259604642255 Temperature: 0.5 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.06153952053405046 generated: nothing generated_algorithm: nothing                   Computing... 66%|████████████████▌ | ETA: 0:00:03 (11.96 ms/it) smc: diagnostics iter: 1065 Avgℓobjective: -1869.6638163787422 Temperature: 0.5 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.796321968435725 generated: nothing generated_algorithm: nothing                   Computing... 68%|█████████████████▏ | ETA: 0:00:03 (11.82 ms/it) mcmc: diagnostics iter: 69 logobjective: -1868.8089026599505 Temperature: 0.5 accepted: true acceptancerate: 1.2140487627005256e-10 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 3 ℓH: -1870.3892070094269                         Computing... 70%|█████████████████▌ | ETA: 0:00:03 (11.77 ms/it) mcmc: diagnostics iter: 70 logobjective: -1868.9205812358655 Temperature: 0.5 accepted: true acceptancerate: 5.170021836071082e-12 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 3 ℓH: -1869.0555254638105                         Computing... 72%|██████████████████ | ETA: 0:00:03 (11.56 ms/it) smc: diagnostics iter: 1072 Avgℓobjective: -1870.031962760515 Temperature: 0.5 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.9046894163851898 generated: nothing generated_algorithm: nothing                   Computing... 74%|██████████████████▋ | ETA: 0:00:02 (11.40 ms/it) mcmc: diagnostics iter: 75 logobjective: -1868.2800989563395 Temperature: 0.5 accepted: true acceptancerate: 1.8033692929569928e-14 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 2 ℓH: -1869.4458515276872                         Computing... 76%|███████████████████▏ | ETA: 0:00:02 (11.34 ms/it) mcmc: diagnostics iter: 77 logobjective: -1867.7682304091563 Temperature: 0.5 accepted: true acceptancerate: 3.831991499161607e-6 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 1 ℓH: -1868.1840228057947                         Computing... 78%|███████████████████▌ | ETA: 0:00:02 (11.39 ms/it) smc: diagnostics iter: 1077 Avgℓobjective: -1869.2234899727487 Temperature: 0.5 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.7746124885668124 generated: nothing generated_algorithm: nothing                   Computing... 83%|████████████████████▋ | ETA: 0:00:02 (11.25 ms/it) mcmc: diagnostics iter: 83 logobjective: -1867.671352145668 Temperature: 0.5 accepted: true acceptancerate: 0.07181687090443142 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 1 ℓH: -1867.8402799760627                         Computing... 86%|█████████████████████▌ | ETA: 0:00:01 (11.03 ms/it) mcmc: diagnostics iter: 86 logobjective: -1869.7401227590965 Temperature: 0.5 accepted: true acceptancerate: 0.005640158396490912 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 3 ℓH: -1869.81869320284                         Computing... 88%|██████████████████████ | ETA: 0:00:01 (10.92 ms/it) mcmc: diagnostics iter: 89 logobjective: -1869.5856156115271 Temperature: 0.5 accepted: true acceptancerate: 7.763515979063162e-27 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 1 ℓH: -1871.8251362556973                         Computing... 90%|██████████████████████▌ | ETA: 0:00:01 (10.89 ms/it) smc: diagnostics iter: 1089 Avgℓobjective: -1870.2480598227667 Temperature: 0.5 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.7392678856356504 generated: nothing generated_algorithm: nothing                   Computing... 92%|███████████████████████ | ETA: 0:00:01 (10.80 ms/it) smc: diagnostics iter: 1091 Avgℓobjective: -1869.7751706809704 Temperature: 0.5 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.4417472152594027 generated: nothing generated_algorithm: nothing                   Computing... 94%|███████████████████████▌ | ETA: 0:00:01 (10.74 ms/it) smc: diagnostics iter: 1093 Avgℓobjective: -1869.8803564375582 Temperature: 0.5 ESS: 4.0 resampled: true AvgJitterCorrelation: -0.10227341808486878 generated: nothing generated_algorithm: nothing                   Computing... 96%|████████████████████████ | ETA: 0:00:00 (10.60 ms/it) smc: diagnostics iter: 1096 Avgℓobjective: -1869.2514826913646 Temperature: 0.5 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.6416821258998611 generated: nothing generated_algorithm: nothing                   Computing... 98%|████████████████████████▋| ETA: 0:00:00 (10.53 ms/it) smc: diagnostics iter: 1098 Avgℓobjective: -1870.707308356723 Temperature: 0.5 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.6405939396425762 generated: nothing generated_algorithm: nothing                   Computing... 100%|█████████████████████████| Time: 0:00:08 (10.47 ms/it) smc: diagnostics iter: 1099 Avgℓobjective: -1869.5014787622765 Temperature: 0.5 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.04143695120250035 generated: nothing generated_algorithm: nothing Sampling finished, printing diagnostics and saving trace. ##################################################################################### ########################################## Chain 1: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -12953.685, Avg. final ℓposterior: -1868.566. NUTS sampler had 39 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 2.033 (1) number of steps and depth of 0.911 (1). Divergences in: Warmup: 36, Adaptionˢˡᵒʷ: 3, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 2: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -3981.108, Avg. final ℓposterior: -1867.754. NUTS sampler had 41 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 1.856 (1) number of steps and depth of 0.867 (1). Divergences in: Warmup: 37, Adaptionˢˡᵒʷ: 4, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 3: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -8673.705, Avg. final ℓposterior: -1868.127. NUTS sampler had 36 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 2.022 (3) number of steps and depth of 0.911 (1). Divergences in: Warmup: 33, Adaptionˢˡᵒʷ: 3, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 4: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -8959.703, Avg. final ℓposterior: -1869.123. NUTS sampler had 37 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 2.089 (3) number of steps and depth of 0.944 (1). Divergences in: Warmup: 33, Adaptionˢˡᵒʷ: 4, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ##################################################################################### ########################################## Chain 1: SMC Diagnostics: SMC algorithm with jitter kernel MCMC Diagnostics: Sampler finished after 90 iterations with average acceptance ratio of 0.0%. Initial average ℓlikelihood per particle: -10426.685, variance: 7.272574302e6 Final average ℓlikelihood per particle: -1871.63, variance: 0.353 Total number of jittering steps: 191. Rejuvenations on average every 1.0 step, every 1.0 steps in first half, every 1.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.409, 0.145, 0.522, 0.72, 0.966]. Quantiles for average number rejuvenation steps: [1.0, 1.0, 1.0, 2.0, 8.775]. Quantiles for ESS: [4.0, 4.0, 4.0, 4.0, 4.0] for 4 chains. ########################################## Chain 2: SMC Diagnostics: SMC algorithm with jitter kernel MCMC Diagnostics: Sampler finished after 90 iterations with average acceptance ratio of 0.0%. Initial average ℓlikelihood per particle: -6122.054, variance: 1.5989613485e7 Final average ℓlikelihood per particle: -1869.912, variance: 1.308 Total number of jittering steps: 265. Rejuvenations on average every 1.0 step, every 1.0 steps in first half, every 1.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.326, 0.138, 0.495, 0.782, 0.966]. Quantiles for average number rejuvenation steps: [1.0, 1.0, 1.0, 3.0, 10.0]. Quantiles for ESS: [4.0, 4.0, 4.0, 4.0, 4.0] for 4 chains. ########################################## Chain 3: SMC Diagnostics: SMC algorithm with jitter kernel MCMC Diagnostics: Sampler finished after 90 iterations with average acceptance ratio of 0.0%. Initial average ℓlikelihood per particle: -8329.162, variance: 2.612735863e7 Final average ℓlikelihood per particle: -1870.057, variance: 2.694 Total number of jittering steps: 239. Rejuvenations on average every 1.0 step, every 1.0 steps in first half, every 1.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.489, 0.174, 0.561, 0.846, 0.977]. Quantiles for average number rejuvenation steps: [1.0, 1.0, 1.0, 2.0, 10.0]. Quantiles for ESS: [4.0, 4.0, 4.0, 4.0, 4.0] for 4 chains. ########################################## Chain 4: SMC Diagnostics: SMC algorithm with jitter kernel MCMC Diagnostics: Sampler finished after 90 iterations with average acceptance ratio of 0.0%. Initial average ℓlikelihood per particle: -6337.598, variance: 2.1188930828e7 Final average ℓlikelihood per particle: -1869.501, variance: 0.572 Total number of jittering steps: 151. Rejuvenations on average every 1.0 step, every 1.0 steps in first half, every 1.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.464, 0.133, 0.575, 0.835, 0.971]. Quantiles for average number rejuvenation steps: [1.0, 1.0, 1.0, 2.0, 6.0]. Quantiles for ESS: [4.0, 4.0, 4.0, 4.0, 4.0] for 4 chains. ┌───┬───────┬───────┬────────┬────────┬───────┬───────┬────────┬────────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼───────┼───────┼────────┼────────┼───────┼───────┼────────┼────────┼──────────┼──────────┼───────┤ │ μ │ 0.266 │ 0.428 │ 0.026 │ -0.533 │ 0.016 │ 0.202 │ 0.56 │ 1.162 │ 290.086 │ 97.004 │ 1.016 │ │ σ │ 9.25 │ 2.391 │ 0.365 │ 2.307 │ 9.675 │ 9.976 │ 10.221 │ 10.769 │ 115.568 │ 56.951 │ 1.04 │ └───┴───────┴───────┴────────┴────────┴───────┴───────┴────────┴────────┴──────────┴──────────┴───────┘ Sampling starts... Computing... 0%| | ETA: 0:03:52 ( 0.29 s/it) smc: diagnostics iter: 1100 Avgℓobjective: -1455.188153204078 Temperature: 0.5 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.11253800338883668 generated: nothing generated_algorithm: nothing                   Computing... 7%|█▊ | ETA: 0:00:11 (14.62 ms/it) smc: diagnostics iter: 1106 Avgℓobjective: -811.9622292527167 Temperature: 0.5 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.971697683162638 generated: nothing generated_algorithm: nothing                   Computing... 13%|███▎ | ETA: 0:00:06 ( 8.77 ms/it) smc: diagnostics iter: 1112 Avgℓobjective: -782.1704380713254 Temperature: 0.5 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.9568334614800706 generated: nothing generated_algorithm: nothing                   Computing... 27%|██████▊ | ETA: 0:00:03 ( 4.57 ms/it) smc: diagnostics iter: 1127 Avgℓobjective: -780.9082748932168 Temperature: 0.5 ESS: 4.0 resampled: true AvgJitterCorrelation: -0.2791575481972781 generated: nothing generated_algorithm: nothing                   Computing... 45%|███████████▎ | ETA: 0:00:01 ( 3.06 ms/it) mcmc: diagnostics iter: 145 logobjective: -780.3845683583003 Temperature: 0.5 accepted: true acceptancerate: 2.971495737343319e-235 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 1 ℓH: -782.3323039365754                         Computing... 62%|███████████████▋ | ETA: 0:00:01 ( 2.41 ms/it) mcmc: diagnostics iter: 163 logobjective: -780.4718422190484 Temperature: 0.5 accepted: true acceptancerate: 2.738343448596049e-21 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 1 ℓH: -782.2278110221689                         Computing... 86%|█████████████████████▌ | ETA: 0:00:00 ( 1.90 ms/it) smc: diagnostics iter: 1185 Avgℓobjective: -780.6288268245597 Temperature: 0.5 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.11793068108173352 generated: nothing generated_algorithm: nothing                   Computing... 100%|█████████████████████████| Time: 0:00:01 ( 1.71 ms/it) smc: diagnostics iter: 1199 Avgℓobjective: -780.8554534376754 Temperature: 0.5 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.3581336159018975 generated: nothing generated_algorithm: nothing Sampling finished, printing diagnostics. ##################################################################################### ########################################## Chain 1: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -783.872, Avg. final ℓposterior: -780.544. NUTS sampler had 29 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 1.7 (1) number of steps and depth of 1.0 (1). Divergences in: Warmup: 24, Adaptionˢˡᵒʷ: 5, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 2: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -780.575, Avg. final ℓposterior: -780.196. NUTS sampler had 28 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 1.644 (1) number of steps and depth of 1.022 (1). Divergences in: Warmup: 22, Adaptionˢˡᵒʷ: 6, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 3: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -783.701, Avg. final ℓposterior: -780.206. NUTS sampler had 32 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 1.778 (1) number of steps and depth of 0.978 (1). Divergences in: Warmup: 26, Adaptionˢˡᵒʷ: 6, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 4: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -781.244, Avg. final ℓposterior: -780.505. NUTS sampler had 26 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 1.667 (1) number of steps and depth of 0.989 (1). Divergences in: Warmup: 23, Adaptionˢˡᵒʷ: 3, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ##################################################################################### ########################################## Chain 1: SMC Diagnostics: SMC algorithm with jitter kernel MCMC Diagnostics: Sampler finished after 90 iterations with average acceptance ratio of 0.0%. Initial average ℓlikelihood per particle: -799.697, variance: 1339.984 Final average ℓlikelihood per particle: -781.666, variance: 2.061 Total number of jittering steps: 193. Rejuvenations on average every 1.0 step, every 1.0 steps in first half, every 1.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.41, 0.199, 0.536, 0.798, 0.966]. Quantiles for average number rejuvenation steps: [1.0, 1.0, 1.0, 2.0, 8.0]. Quantiles for ESS: [4.0, 4.0, 4.0, 4.0, 4.0] for 4 chains. ########################################## Chain 2: SMC Diagnostics: SMC algorithm with jitter kernel MCMC Diagnostics: Sampler finished after 90 iterations with average acceptance ratio of 0.0%. Initial average ℓlikelihood per particle: -794.661, variance: 759.6 Final average ℓlikelihood per particle: -780.469, variance: 0.198 Total number of jittering steps: 121. Rejuvenations on average every 1.0 step, every 1.0 steps in first half, every 1.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.289, 0.155, 0.54, 0.722, 0.957]. Quantiles for average number rejuvenation steps: [1.0, 1.0, 1.0, 1.0, 3.0]. Quantiles for ESS: [4.0, 4.0, 4.0, 4.0, 4.0] for 4 chains. ########################################## Chain 3: SMC Diagnostics: SMC algorithm with jitter kernel MCMC Diagnostics: Sampler finished after 90 iterations with average acceptance ratio of 0.0%. Initial average ℓlikelihood per particle: -789.035, variance: 277.561 Final average ℓlikelihood per particle: -780.76, variance: 0.366 Total number of jittering steps: 158. Rejuvenations on average every 1.0 step, every 1.0 steps in first half, every 1.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.237, 0.267, 0.612, 0.848, 0.96]. Quantiles for average number rejuvenation steps: [1.0, 1.0, 1.0, 2.0, 4.0]. Quantiles for ESS: [4.0, 4.0, 4.0, 4.0, 4.0] for 4 chains. ########################################## Chain 4: SMC Diagnostics: SMC algorithm with jitter kernel MCMC Diagnostics: Sampler finished after 90 iterations with average acceptance ratio of 0.0%. Initial average ℓlikelihood per particle: -781.437, variance: 0.732 Final average ℓlikelihood per particle: -780.855, variance: 1.268 Total number of jittering steps: 94. Rejuvenations on average every 1.0 step, every 1.0 steps in first half, every 1.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.585, -0.03, 0.253, 0.577, 0.906]. Quantiles for average number rejuvenation steps: [1.0, 1.0, 1.0, 1.0, 2.0]. Quantiles for ESS: [4.0, 4.0, 4.0, 4.0, 4.0] for 4 chains. ┌───┬────────┬───────┬────────┬───────┬────────┬────────┬────────┬───────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼────────┼───────┼────────┼───────┼────────┼────────┼────────┼───────┼──────────┼──────────┼───────┤ │ μ │ -0.073 │ 0.041 │ 0.002 │ -0.15 │ -0.103 │ -0.077 │ -0.042 │ 0.006 │ 280.196 │ 299.249 │ 1.001 │ │ σ │ 0.999 │ 0.034 │ 0.002 │ 0.942 │ 0.981 │ 0.999 │ 1.021 │ 1.051 │ 239.341 │ 259.2 │ 1.012 │ └───┴────────┴───────┴────────┴───────┴────────┴────────┴────────┴───────┴──────────┴──────────┴───────┘ Constructing new sampler... Sampling starts... Computing... 0%|▏ | ETA: 0:03:13 ( 0.48 s/it) mcmc: diagnostics iter: 1 logobjective: -1868.1259984399285 Temperature: 0.5 accepted: true acceptancerate: 0.25017795818851435 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 3 ℓH: -1868.5039789215746                         Computing... 100%|█████████████████████████| Time: 0:00:01 ( 3.12 ms/it) mcmc: diagnostics iter: 100 logobjective: -2044.0363103256977 Temperature: 0.5460980646457352 accepted: true acceptancerate: 0.9999354448413731 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 127 ℓH: -2044.5970601027022 Sampling finished, printing diagnostics and saving trace. ##################################################################################### ########################################## Chain 1: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1885.976, Avg. final ℓposterior: -2040.15. NUTS sampler had 22 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 18.689 (127) number of steps and depth of 2.122 (6). Divergences in: Warmup: 22, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 2: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1886.578, Avg. final ℓposterior: -2042.236. NUTS sampler had 27 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 15.611 (31) number of steps and depth of 2.089 (5). Divergences in: Warmup: 27, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 3: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1886.002, Avg. final ℓposterior: -2040.588. NUTS sampler had 29 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 20.589 (15) number of steps and depth of 2.111 (3). Divergences in: Warmup: 29, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 4: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1885.84, Avg. final ℓposterior: -2044.036. NUTS sampler had 16 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 34.844 (127) number of steps and depth of 2.367 (6). Divergences in: Warmup: 16, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ┌───┬────────┬───────┬────────┬────────┬───────┬───────┬────────┬────────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼────────┼───────┼────────┼────────┼───────┼───────┼────────┼────────┼──────────┼──────────┼───────┤ │ μ │ 0.208 │ 0.302 │ 0.068 │ -0.331 │ 0.055 │ 0.203 │ 0.296 │ 1.022 │ 15.415 │ 21.588 │ 1.263 │ │ σ │ 10.049 │ 0.307 │ 0.054 │ 9.586 │ 9.849 │ 9.995 │ 10.259 │ 10.626 │ 40.749 │ 20.094 │ 1.109 │ └───┴────────┴───────┴────────┴────────┴───────┴───────┴────────┴────────┴──────────┴──────────┴───────┘ Sampling starts... Computing... 0%|▏ | ETA: 0:01:32 ( 0.23 s/it) mcmc: diagnostics iter: 101 logobjective: -2041.8451445979915 Temperature: 0.5465413282544795 accepted: true acceptancerate: 0.9997426135173805 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 111 ℓH: -2042.9628712872404                         Computing... 11%|██▊ | ETA: 0:00:05 (12.86 ms/it) mcmc: diagnostics iter: 111 logobjective: -2058.1286625553057 Temperature: 0.550950225852198 accepted: true acceptancerate: 0.9996434868276112 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 31 ℓH: -2059.2743692212734                         Computing... 21%|█████▎ | ETA: 0:00:03 ( 8.11 ms/it) mcmc: diagnostics iter: 122 logobjective: -2078.5831104491895 Temperature: 0.5557505179950155 accepted: true acceptancerate: 0.9976741730084342 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 31 ℓH: -2079.446616420768                         Computing... 50%|████████████▌ | ETA: 0:00:01 ( 3.96 ms/it) mcmc: diagnostics iter: 151 logobjective: -2122.803167975117 Temperature: 0.5681612946636618 accepted: true acceptancerate: 0.9847642652652445 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 11 ℓH: -2125.1323753089714                         Computing... 97%|████████████████████████▎| ETA: 0:00:00 ( 2.32 ms/it) mcmc: diagnostics iter: 197 logobjective: -2193.1565300295674 Temperature: 0.5871400928911229 accepted: true acceptancerate: 0.9978193159815207 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 31 ℓH: -2194.869666844753                         Computing... 100%|█████████████████████████| Time: 0:00:00 ( 2.26 ms/it) mcmc: diagnostics iter: 200 logobjective: -2199.555211194648 Temperature: 0.5883484625830675 accepted: true acceptancerate: 0.9868989599222585 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 23 ℓH: -2200.492433211325 Sampling finished, printing diagnostics. ##################################################################################### ########################################## Chain 1: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -2058.772, Avg. final ℓposterior: -2201.15. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 19.6 (15) number of steps and depth of 3.667 (4). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 2: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -2059.377, Avg. final ℓposterior: -2197.999. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 21.467 (15) number of steps and depth of 3.644 (3). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 3: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -2059.128, Avg. final ℓposterior: -2199.59. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 33.489 (3) number of steps and depth of 4.189 (2). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 4: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -2058.129, Avg. final ℓposterior: -2199.555. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 35.911 (23) number of steps and depth of 4.089 (4). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ┌───┬────────┬───────┬────────┬────────┬───────┬───────┬───────┬────────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼────────┼───────┼────────┼────────┼───────┼───────┼───────┼────────┼──────────┼──────────┼───────┤ │ μ │ 0.311 │ 0.38 │ 0.037 │ -0.465 │ 0.069 │ 0.301 │ 0.508 │ 1.142 │ 112.346 │ 85.324 │ 1.018 │ │ σ │ 10.048 │ 0.289 │ 0.022 │ 9.536 │ 9.855 │ 10.04 │ 10.25 │ 10.643 │ 174.746 │ 193.803 │ 1.014 │ └───┴────────┴───────┴────────┴────────┴───────┴───────┴───────┴────────┴──────────┴──────────┴───────┘ Constructing new sampler... Sampling starts... Computing... 0%|▏ | ETA: 0:02:03 ( 0.31 s/it) smc: diagnostics iter: 1000 Avgℓobjective: -1869.1138320694351 Temperature: 0.5 ESS: 4.0 resampled: true AvgJitterCorrelation: 0.7306022417320018 generated: nothing generated_algorithm: nothing                   Computing... 26%|██████▍ | ETA: 0:00:02 ( 7.06 ms/it) smc: diagnostics iter: 1025 Avgℓobjective: -1914.6317266609885 Temperature: 0.5120650453944637 ESS: 3.999999792735914 resampled: true AvgJitterCorrelation: 0.579365421444566 generated: nothing generated_algorithm: nothing                   Computing... 50%|████████████▌ | ETA: 0:00:01 ( 4.71 ms/it) smc: diagnostics iter: 1049 Avgℓobjective: -1957.5499538824392 Temperature: 0.5233735045862593 ESS: 3.999999587376469 resampled: true AvgJitterCorrelation: 0.21402769571245867 generated: nothing generated_algorithm: nothing                   Computing... 67%|████████████████▊ | ETA: 0:00:01 ( 3.87 ms/it) smc: diagnostics iter: 1067 Avgℓobjective: -1988.2449599534261 Temperature: 0.5316825199883755 ESS: 3.999999883210542 resampled: true AvgJitterCorrelation: 0.14359547682355095 generated: nothing generated_algorithm: nothing                   Computing... 90%|██████████████████████▍ | ETA: 0:00:00 ( 3.20 ms/it) smc: diagnostics iter: 1089 Avgℓobjective: -2025.7299475116372 Temperature: 0.5416415271579234 ESS: 3.9999993399181357 resampled: true AvgJitterCorrelation: 0.3607973632960826 generated: nothing generated_algorithm: nothing                   Computing... 100%|█████████████████████████| Time: 0:00:01 ( 2.97 ms/it) smc: diagnostics iter: 1099 Avgℓobjective: -2043.3361829315572 Temperature: 0.5460980646457352 ESS: 3.9999999407483733 resampled: true AvgJitterCorrelation: 0.4759801679191281 generated: nothing generated_algorithm: nothing Sampling finished, printing diagnostics and saving trace. ##################################################################################### SMC algorithm with jitter kernel MCMC Diagnostics: Sampler finished after 90 iterations with average acceptance ratio of 0.0%. Initial average ℓlikelihood per particle: -1887.914, variance: 0.14 Final average ℓlikelihood per particle: -2043.336, variance: 6.201 Total number of jittering steps: 120. Rejuvenations on average every 1.0 step, every 1.0 steps in first half, every 1.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.421, 0.008, 0.354, 0.742, 0.974]. Quantiles for average number rejuvenation steps: [1.0, 1.0, 1.0, 1.0, 3.775]. Quantiles for ESS: [4.0, 4.0, 4.0, 4.0, 4.0] for 4 chains. ┌───┬────────┬───────┬────────┬────────┬───────┬────────┬────────┬────────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼────────┼───────┼────────┼────────┼───────┼────────┼────────┼────────┼──────────┼──────────┼───────┤ │ μ │ 0.275 │ 0.357 │ 0.035 │ -0.439 │ 0.05 │ 0.3 │ 0.538 │ 0.889 │ 110.101 │ 99.456 │ 1.046 │ │ σ │ 10.046 │ 0.306 │ 0.018 │ 9.47 │ 9.808 │ 10.048 │ 10.253 │ 10.652 │ 269.321 │ 175.906 │ 1.026 │ └───┴────────┴───────┴────────┴────────┴───────┴────────┴────────┴────────┴──────────┴──────────┴───────┘ Sampling starts... Computing... 62%|███████████████▍ | ETA: 0:00:00 ( 0.51 ms/it) smc: diagnostics iter: 1161 Avgℓobjective: -897.7275757969358 Temperature: 0.572777602395081 ESS: 3.999997539152828 resampled: true AvgJitterCorrelation: 0.10205233524654062 generated: nothing generated_algorithm: nothing                   Computing... 100%|█████████████████████████| Time: 0:00:00 ( 0.99 ms/it) smc: diagnostics iter: 1199 Avgℓobjective: -922.2384485679237 Temperature: 0.5883484625830675 ESS: 3.9999982426125498 resampled: true AvgJitterCorrelation: -0.11059342999140956 generated: nothing generated_algorithm: nothing Sampling finished, printing diagnostics. ##################################################################################### SMC algorithm with jitter kernel MCMC Diagnostics: Sampler finished after 90 iterations with average acceptance ratio of 0.0%. Initial average ℓlikelihood per particle: -864.827, variance: 2.741 Final average ℓlikelihood per particle: -922.238, variance: 0.106 Total number of jittering steps: 226. Rejuvenations on average every 1.0 step, every 1.0 steps in first half, every 1.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.455, 0.104, 0.432, 0.769, 1.0]. Quantiles for average number rejuvenation steps: [1.0, 1.0, 1.0, 2.0, 10.0]. Quantiles for ESS: [4.0, 4.0, 4.0, 4.0, 4.0] for 4 chains. ┌───┬────────┬───────┬────────┬────────┬────────┬────────┬───────┬───────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼────────┼───────┼────────┼────────┼────────┼────────┼───────┼───────┼──────────┼──────────┼───────┤ │ μ │ -0.009 │ 0.042 │ 0.003 │ -0.089 │ -0.033 │ -0.007 │ 0.017 │ 0.078 │ 146.136 │ 140.362 │ 1.061 │ │ σ │ 1.0 │ 0.03 │ 0.003 │ 0.947 │ 0.975 │ 0.999 │ 1.021 │ 1.06 │ 97.542 │ 74.518 │ 1.098 │ └───┴────────┴───────┴────────┴────────┴────────┴────────┴───────┴───────┴──────────┴──────────┴───────┘ Constructing new sampler... Sampling starts... Computing... 0%| | ETA: 0:08:35 ( 0.65 s/it) smc: diagnostics iter: 1000 Avgℓobjective: -24126.353531121742 Temperature: 0.5 ESS: 4.0 resampled: true AvgJitterCorrelation: NaN generated: nothing generated_algorithm: nothing                   Computing... 19%|████▊ | ETA: 0:00:11 (16.43 ms/it) smc: diagnostics iter: 1018 Avgℓobjective: -3027.007152610879 Temperature: 0.5087164850066754 ESS: 3.270776833411365 resampled: true AvgJitterCorrelation: 0.9545074175323276 generated: nothing generated_algorithm: nothing                   Computing... 20%|█████▏ | ETA: 0:00:12 (18.19 ms/it) smc: diagnostics iter: 1020 Avgℓobjective: -1905.7994725039534 Temperature: 0.5096755545974264 ESS: 3.9999990437551722 resampled: true AvgJitterCorrelation: 0.7284728088888037 generated: nothing generated_algorithm: nothing                   Computing... 21%|█████▎ | ETA: 0:00:13 (20.81 ms/it) smc: diagnostics iter: 1020 Avgℓobjective: -2107.0992544419046 Temperature: 0.5096755545974264 ESS: 3.4933412339718095 resampled: true AvgJitterCorrelation: 0.578931137961676 generated: nothing generated_algorithm: nothing                   Computing... 24%|█████▉ | ETA: 0:00:13 (21.77 ms/it) smc: diagnostics iter: 1023 Avgℓobjective: -1912.0310706854261 Temperature: 0.511110649623226 ESS: 3.9999997306278465 resampled: true AvgJitterCorrelation: 0.8126960494758768 generated: nothing generated_algorithm: nothing                   Computing... 24%|██████▏ | ETA: 0:00:13 (21.69 ms/it) smc: diagnostics iter: 1024 Avgℓobjective: -1912.9693650114073 Temperature: 0.5115880806294534 ESS: 3.9999986809856307 resampled: true AvgJitterCorrelation: 0.9481232040122038 generated: nothing generated_algorithm: nothing                   Computing... 25%|██████▎ | ETA: 0:00:13 (21.80 ms/it) mcmc: diagnostics iter: 26 logobjective: -1913.9554365312474 Temperature: 0.5120650453944637 accepted: true acceptancerate: 1.5103738776431722e-14 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 1 ℓH: -1914.5680833803435                         Computing... 26%|██████▌ | ETA: 0:00:13 (21.77 ms/it) mcmc: diagnostics iter: 26 logobjective: -2453.030994775604 Temperature: 0.5120650453944637 accepted: true acceptancerate: 0.0 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 1 ℓH: -2453.890921238501                         Computing... 27%|██████▊ | ETA: 0:00:13 (21.98 ms/it) smc: diagnostics iter: 1026 Avgℓobjective: -1916.6634838979064 Temperature: 0.5125415443735707 ESS: 3.999998555800424 resampled: true AvgJitterCorrelation: 0.5955730684043751 generated: nothing generated_algorithm: nothing                   Computing... 28%|███████ | ETA: 0:00:13 (21.79 ms/it) mcmc: diagnostics iter: 28 logobjective: -1916.6169645434595 Temperature: 0.5130175780216433 accepted: true acceptancerate: 2.7360360615606054e-6 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 3 ℓH: -1916.6884290964538                         Computing... 29%|███████▎ | ETA: 0:00:12 (21.50 ms/it) smc: diagnostics iter: 1028 Avgℓobjective: -2056.9881445432393 Temperature: 0.5134931467931065 ESS: 3.861985459711212 resampled: true AvgJitterCorrelation: 0.9959394471174596 generated: nothing generated_algorithm: nothing                   Computing... 36%|████████▉ | ETA: 0:00:09 (18.04 ms/it) smc: diagnostics iter: 1035 Avgℓobjective: -1933.0574178962286 Temperature: 0.5168091497268879 ESS: 3.999996473325086 resampled: true AvgJitterCorrelation: 0.2707183871989608 generated: nothing generated_algorithm: nothing                   Computing... 43%|██████████▊ | ETA: 0:00:07 (15.19 ms/it) smc: diagnostics iter: 1042 Avgℓobjective: -1944.8141885575278 Temperature: 0.5201025509740036 ESS: 3.9999996841660383 resampled: true AvgJitterCorrelation: -0.1511216351907188 generated: nothing generated_algorithm: nothing                   Computing... 52%|█████████████ | ETA: 0:00:05 (12.83 ms/it) smc: diagnostics iter: 1051 Avgℓobjective: -1960.6575899068052 Temperature: 0.5243039611636671 ESS: 3.999999996989672 resampled: true AvgJitterCorrelation: -0.5390788084367976 generated: nothing generated_algorithm: nothing                   Computing... 60%|███████████████▏ | ETA: 0:00:04 (11.29 ms/it) smc: diagnostics iter: 1060 Avgℓobjective: -1975.9783191715078 Temperature: 0.528468588812357 ESS: 3.999995767866808 resampled: true AvgJitterCorrelation: 0.7399597096430525 generated: nothing generated_algorithm: nothing                   Computing... 68%|████████████████▉ | ETA: 0:00:03 (10.31 ms/it) smc: diagnostics iter: 1067 Avgℓobjective: -1987.7618251513372 Temperature: 0.5316825199883755 ESS: 3.9999988844490715 resampled: true AvgJitterCorrelation: 0.3376426381802845 generated: nothing generated_algorithm: nothing                   Computing... 75%|██████████████████▊ | ETA: 0:00:02 ( 9.70 ms/it) mcmc: diagnostics iter: 76 logobjective: -1999.886765741416 Temperature: 0.535328769269961 accepted: true acceptancerate: 0.5053687258824204 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 3 ℓH: -1999.8982017007115                         Computing... 82%|████████████████████▌ | ETA: 0:00:01 ( 9.02 ms/it) smc: diagnostics iter: 1082 Avgℓobjective: -2013.2170764488246 Temperature: 0.5384959418476701 ESS: 3.9999991746115535 resampled: true AvgJitterCorrelation: 0.9754326890919717 generated: nothing generated_algorithm: nothing                   Computing... 90%|██████████████████████▍ | ETA: 0:00:01 ( 8.43 ms/it) smc: diagnostics iter: 1089 Avgℓobjective: -2024.8164827549122 Temperature: 0.5416415271579234 ESS: 3.999997654868439 resampled: true AvgJitterCorrelation: 0.2204580804549507 generated: nothing generated_algorithm: nothing                   Computing... 96%|████████████████████████▏| ETA: 0:00:00 ( 7.97 ms/it) smc: diagnostics iter: 1096 Avgℓobjective: -2037.2031435566328 Temperature: 0.5447656723383025 ESS: 3.999999221877697 resampled: true AvgJitterCorrelation: -0.25479038255088926 generated: nothing generated_algorithm: nothing                   Computing... 100%|█████████████████████████| Time: 0:00:06 ( 7.76 ms/it) smc: diagnostics iter: 1099 Avgℓobjective: -2041.451788801196 Temperature: 0.5460980646457352 ESS: 3.9999998502975127 resampled: true AvgJitterCorrelation: 0.8075792018177325 generated: nothing generated_algorithm: nothing Sampling finished, printing diagnostics and saving trace. ##################################################################################### ########################################## Chain 1: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -5178.822, Avg. final ℓposterior: -2039.855. NUTS sampler had 30 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 2.1 (3) number of steps and depth of 0.956 (1). Divergences in: Warmup: 28, Adaptionˢˡᵒʷ: 2, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 2: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -8730.038, Avg. final ℓposterior: -2039.972. NUTS sampler had 29 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 2.133 (6) number of steps and depth of 1.0 (2). Divergences in: Warmup: 28, Adaptionˢˡᵒʷ: 1, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 3: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -6330.262, Avg. final ℓposterior: -2040.178. NUTS sampler had 36 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 2.056 (7) number of steps and depth of 0.978 (2). Divergences in: Warmup: 31, Adaptionˢˡᵒʷ: 5, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 4: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -6549.108, Avg. final ℓposterior: -2039.921. NUTS sampler had 36 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 1.711 (1) number of steps and depth of 0.867 (1). Divergences in: Warmup: 33, Adaptionˢˡᵒʷ: 3, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ##################################################################################### ########################################## Chain 1: SMC Diagnostics: SMC algorithm with jitter kernel MCMC Diagnostics: Sampler finished after 90 iterations with average acceptance ratio of 0.0%. Initial average ℓlikelihood per particle: -5052.002, variance: 2.231030527e6 Final average ℓlikelihood per particle: -2041.752, variance: 0.618 Total number of jittering steps: 137. Rejuvenations on average every 1.0 step, every 1.0 steps in first half, every 1.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.266, 0.248, 0.557, 0.762, 0.975]. Quantiles for average number rejuvenation steps: [1.0, 1.0, 1.0, 1.0, 6.55]. Quantiles for ESS: [3.229, 4.0, 4.0, 4.0, 4.0] for 4 chains. ########################################## Chain 2: SMC Diagnostics: SMC algorithm with jitter kernel MCMC Diagnostics: Sampler finished after 90 iterations with average acceptance ratio of 0.0%. Initial average ℓlikelihood per particle: -7488.147, variance: 402225.899 Final average ℓlikelihood per particle: -2042.68, variance: 2.452 Total number of jittering steps: 151. Rejuvenations on average every 1.0 step, every 1.0 steps in first half, every 1.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.275, 0.165, 0.55, 0.744, 0.967]. Quantiles for average number rejuvenation steps: [1.0, 1.0, 1.0, 2.0, 5.0]. Quantiles for ESS: [3.42, 4.0, 4.0, 4.0, 4.0] for 4 chains. ########################################## Chain 3: SMC Diagnostics: SMC algorithm with jitter kernel MCMC Diagnostics: Sampler finished after 90 iterations with average acceptance ratio of 0.0%. Initial average ℓlikelihood per particle: -5683.811, variance: 2.837471615e6 Final average ℓlikelihood per particle: -2042.067, variance: 0.741 Total number of jittering steps: 179. Rejuvenations on average every 1.0 step, every 1.0 steps in first half, every 1.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.302, 0.213, 0.562, 0.785, 0.958]. Quantiles for average number rejuvenation steps: [1.0, 1.0, 1.0, 2.0, 6.775]. Quantiles for ESS: [3.446, 4.0, 4.0, 4.0, 4.0] for 4 chains. ########################################## Chain 4: SMC Diagnostics: SMC algorithm with jitter kernel MCMC Diagnostics: Sampler finished after 90 iterations with average acceptance ratio of 0.0%. Initial average ℓlikelihood per particle: -6504.139, variance: 114464.623 Final average ℓlikelihood per particle: -2041.452, variance: 0.054 Total number of jittering steps: 219. Rejuvenations on average every 1.0 step, every 1.0 steps in first half, every 1.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.524, 0.054, 0.398, 0.798, 0.973]. Quantiles for average number rejuvenation steps: [1.0, 1.0, 1.0, 2.0, 10.0]. Quantiles for ESS: [3.253, 4.0, 4.0, 4.0, 4.0] for 4 chains. ┌───┬───────┬───────┬────────┬────────┬────────┬───────┬────────┬────────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼───────┼───────┼────────┼────────┼────────┼───────┼────────┼────────┼──────────┼──────────┼───────┤ │ μ │ 0.224 │ 0.397 │ 0.04 │ -0.491 │ -0.031 │ 0.215 │ 0.484 │ 1.012 │ 113.829 │ 147.77 │ 1.051 │ │ σ │ 9.706 │ 2.796 │ 0.234 │ 3.41 │ 9.735 │ 9.986 │ 10.212 │ 10.627 │ 114.527 │ 43.327 │ 1.027 │ └───┴───────┴───────┴────────┴────────┴────────┴───────┴────────┴────────┴──────────┴──────────┴───────┘ Sampling starts... Computing... 0%| | ETA: 0:04:01 ( 0.30 s/it) smc: diagnostics iter: 1100 Avgℓobjective: -1146.324842775106 Temperature: 0.5465413282544795 ESS: 3.9999987773896986 resampled: true AvgJitterCorrelation: -0.18933763336825563 generated: nothing generated_algorithm: nothing                   Computing... 14%|███▋ | ETA: 0:00:04 ( 6.09 ms/it) smc: diagnostics iter: 1114 Avgℓobjective: -864.9431576340047 Temperature: 0.5527017587214768 ESS: 3.999998305046548 resampled: true AvgJitterCorrelation: 0.2658817261132981 generated: nothing generated_algorithm: nothing                   Computing... 32%|████████ | ETA: 0:00:02 ( 3.13 ms/it) smc: diagnostics iter: 1132 Avgℓobjective: -877.5858892012569 Temperature: 0.5604994955487097 ESS: 3.999998333401722 resampled: true AvgJitterCorrelation: 0.18018214482787265 generated: nothing generated_algorithm: nothing                   Computing... 52%|████████████▉ | ETA: 0:00:01 ( 2.21 ms/it) mcmc: diagnostics iter: 152 logobjective: -888.9702612153318 Temperature: 0.5685830121493418 accepted: true acceptancerate: 4.7197401363260735e-26 generated: nothing generated_algorithm: nothing NUTS: diagnostics ϵ: 0.1 steps: 1 ℓH: -890.3053185191815                         Computing... 71%|█████████████████▊ | ETA: 0:00:00 ( 1.79 ms/it) smc: diagnostics iter: 1170 Avgℓobjective: -902.8941862531512 Temperature: 0.5765178526051888 ESS: 3.9999974565872884 resampled: true AvgJitterCorrelation: 0.8111172069733912 generated: nothing generated_algorithm: nothing                   Computing... 89%|██████████████████████▎ | ETA: 0:00:00 ( 1.60 ms/it) smc: diagnostics iter: 1188 Avgℓobjective: -913.1828690802632 Temperature: 0.583900404181912 ESS: 3.9999999317268062 resampled: true AvgJitterCorrelation: 0.7615569520670817 generated: nothing generated_algorithm: nothing                   Computing... 100%|█████████████████████████| Time: 0:00:01 ( 1.50 ms/it) smc: diagnostics iter: 1199 Avgℓobjective: -920.6526910343398 Temperature: 0.5883484625830675 ESS: 3.999999455881023 resampled: true AvgJitterCorrelation: 0.34237208087756976 generated: nothing generated_algorithm: nothing Sampling finished, printing diagnostics. ##################################################################################### ########################################## Chain 1: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -862.338, Avg. final ℓposterior: -922.399. NUTS sampler had 34 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 1.767 (1) number of steps and depth of 0.978 (1). Divergences in: Warmup: 27, Adaptionˢˡᵒʷ: 7, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 2: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -863.163, Avg. final ℓposterior: -923.97. NUTS sampler had 36 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 1.711 (1) number of steps and depth of 0.989 (1). Divergences in: Warmup: 31, Adaptionˢˡᵒʷ: 5, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 3: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -869.256, Avg. final ℓposterior: -919.903. NUTS sampler had 29 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 1.567 (1) number of steps and depth of 0.967 (1). Divergences in: Warmup: 23, Adaptionˢˡᵒʷ: 6, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 4: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 90 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -861.543, Avg. final ℓposterior: -920.379. NUTS sampler had 49 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 1.844 (1) number of steps and depth of 0.944 (1). Divergences in: Warmup: 42, Adaptionˢˡᵒʷ: 7, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ##################################################################################### ########################################## Chain 1: SMC Diagnostics: SMC algorithm with jitter kernel MCMC Diagnostics: Sampler finished after 90 iterations with average acceptance ratio of 0.0%. Initial average ℓlikelihood per particle: -862.919, variance: 2.474 Final average ℓlikelihood per particle: -920.467, variance: 0.849 Total number of jittering steps: 106. Rejuvenations on average every 1.0 step, every 1.0 steps in first half, every 1.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.441, 0.14, 0.45, 0.672, 0.962]. Quantiles for average number rejuvenation steps: [1.0, 1.0, 1.0, 1.0, 2.0]. Quantiles for ESS: [4.0, 4.0, 4.0, 4.0, 4.0] for 4 chains. ########################################## Chain 2: SMC Diagnostics: SMC algorithm with jitter kernel MCMC Diagnostics: Sampler finished after 90 iterations with average acceptance ratio of 0.0%. Initial average ℓlikelihood per particle: -862.703, variance: 0.352 Final average ℓlikelihood per particle: -921.865, variance: 3.238 Total number of jittering steps: 97. Rejuvenations on average every 1.0 step, every 1.0 steps in first half, every 1.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.687, -0.008, 0.269, 0.569, 0.931]. Quantiles for average number rejuvenation steps: [1.0, 1.0, 1.0, 1.0, 2.0]. Quantiles for ESS: [4.0, 4.0, 4.0, 4.0, 4.0] for 4 chains. ########################################## Chain 3: SMC Diagnostics: SMC algorithm with jitter kernel MCMC Diagnostics: Sampler finished after 90 iterations with average acceptance ratio of 0.0%. Initial average ℓlikelihood per particle: -863.255, variance: 5.663 Final average ℓlikelihood per particle: -920.483, variance: 0.489 Total number of jittering steps: 120. Rejuvenations on average every 1.0 step, every 1.0 steps in first half, every 1.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.665, 0.039, 0.352, 0.735, 0.925]. Quantiles for average number rejuvenation steps: [1.0, 1.0, 1.0, 1.0, 2.0]. Quantiles for ESS: [4.0, 4.0, 4.0, 4.0, 4.0] for 4 chains. ########################################## Chain 4: SMC Diagnostics: SMC algorithm with jitter kernel MCMC Diagnostics: Sampler finished after 90 iterations with average acceptance ratio of 0.0%. Initial average ℓlikelihood per particle: -861.968, variance: 0.131 Final average ℓlikelihood per particle: -920.653, variance: 0.638 Total number of jittering steps: 207. Rejuvenations on average every 1.0 step, every 1.0 steps in first half, every 1.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.61, -0.045, 0.42, 0.781, 0.974]. Quantiles for average number rejuvenation steps: [1.0, 1.0, 1.0, 2.0, 10.0]. Quantiles for ESS: [4.0, 4.0, 4.0, 4.0, 4.0] for 4 chains. ┌───┬────────┬───────┬────────┬────────┬────────┬────────┬────────┬───────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼────────┼───────┼────────┼────────┼────────┼────────┼────────┼───────┼──────────┼──────────┼───────┤ │ μ │ -0.033 │ 0.041 │ 0.003 │ -0.116 │ -0.061 │ -0.032 │ -0.003 │ 0.043 │ 222.887 │ 231.526 │ 1.011 │ │ σ │ 1.002 │ 0.031 │ 0.002 │ 0.943 │ 0.979 │ 1.0 │ 1.024 │ 1.059 │ 229.834 │ 289.027 │ 1.014 │ └───┴────────┴───────┴────────┴────────┴────────┴────────┴────────┴───────┴──────────┴──────────┴───────┘ Max iterations in Expanding/Rolling datatune set to 900. Iterations in SampleDefault are 500. Sampling iterations set to 500 Constructing new sampler... Sampling starts... Sampling finished, printing diagnostics and saving trace. ##################################################################################### ########################################## Chain 1: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 500 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -382.679, Avg. final ℓposterior: -2253.102. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 15.092 (23) number of steps and depth of 3.308 (4). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 2: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 500 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -383.528, Avg. final ℓposterior: -2253.507. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 15.572 (23) number of steps and depth of 3.36 (4). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 3: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 500 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -383.993, Avg. final ℓposterior: -2253.653. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 14.756 (15) number of steps and depth of 3.262 (4). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 4: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 500 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -384.153, Avg. final ℓposterior: -2253.756. NUTS sampler had 1 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 15.524 (15) number of steps and depth of 3.352 (3). Divergences in: Warmup: 1, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ┌───┬────────┬───────┬────────┬────────┬────────┬────────┬────────┬────────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼────────┼───────┼────────┼────────┼────────┼────────┼────────┼────────┼──────────┼──────────┼───────┤ │ μ │ 0.181 │ 0.536 │ 0.032 │ -0.927 │ -0.175 │ 0.202 │ 0.531 │ 1.185 │ 299.283 │ 249.612 │ 1.024 │ │ σ │ 10.308 │ 0.507 │ 0.052 │ 9.116 │ 10.038 │ 10.332 │ 10.618 │ 11.208 │ 111.471 │ 83.876 │ 1.025 │ └───┴────────┴───────┴────────┴────────┴────────┴────────┴────────┴────────┴──────────┴──────────┴───────┘ Max iterations in Expanding/Rolling datatune set to 400. Iterations in SampleDefault are 500. Sampling iterations set to 400 Sampling starts... Sampling finished, printing diagnostics. ##################################################################################### ########################################## Chain 1: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 400 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -2258.211, Avg. final ℓposterior: -3735.639. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 16.13 (7) number of steps and depth of 3.445 (2). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 2: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 400 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -2257.081, Avg. final ℓposterior: -3737.115. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 18.125 (15) number of steps and depth of 3.592 (4). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 3: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 400 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -2256.878, Avg. final ℓposterior: -3736.134. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 15.385 (15) number of steps and depth of 3.4 (4). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 4: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 400 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -2256.693, Avg. final ℓposterior: -3735.522. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 14.62 (15) number of steps and depth of 3.342 (3). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ┌───┬────────┬───────┬────────┬────────┬────────┬────────┬────────┬────────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼────────┼───────┼────────┼────────┼────────┼────────┼────────┼────────┼──────────┼──────────┼───────┤ │ μ │ 0.181 │ 0.358 │ 0.024 │ -0.515 │ -0.076 │ 0.189 │ 0.424 │ 0.905 │ 217.664 │ 335.817 │ 1.026 │ │ σ │ 10.094 │ 0.281 │ 0.043 │ 9.594 │ 9.89 │ 10.083 │ 10.281 │ 10.704 │ 43.749 │ 602.8 │ 1.064 │ └───┴────────┴───────┴────────┴────────┴────────┴────────┴────────┴────────┴──────────┴──────────┴───────┘ Max iterations in Expanding/Rolling datatune set to 900. Iterations in SampleDefault are 500. Sampling iterations set to 500 Constructing new sampler... Sampling starts... Sampling finished, printing diagnostics and saving trace. ##################################################################################### SMC algorithm with jitter kernel MCMC Diagnostics: Sampler finished after 500 iterations with average acceptance ratio of 0.0%. Initial average ℓlikelihood per particle: -386.829, variance: 3.98 Final average ℓlikelihood per particle: -2256.246, variance: 0.57 Total number of jittering steps: 545. Rejuvenations on average every 1.0 step, every 1.0 steps in first half, every 1.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.622, 0.06, 0.358, 0.669, 0.92]. Quantiles for average number rejuvenation steps: [1.0, 1.0, 1.0, 1.0, 2.0]. Quantiles for ESS: [3.869, 3.988, 3.995, 3.998, 4.0] for 4 chains. ┌───┬────────┬───────┬────────┬────────┬────────┬────────┬────────┬────────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼────────┼───────┼────────┼────────┼────────┼────────┼────────┼────────┼──────────┼──────────┼───────┤ │ μ │ 0.191 │ 0.541 │ 0.035 │ -0.966 │ -0.139 │ 0.223 │ 0.563 │ 1.185 │ 253.726 │ 302.163 │ 1.028 │ │ σ │ 10.323 │ 0.519 │ 0.05 │ 9.046 │ 10.058 │ 10.352 │ 10.629 │ 11.261 │ 124.543 │ 90.461 │ 1.035 │ └───┴────────┴───────┴────────┴────────┴────────┴────────┴────────┴────────┴──────────┴──────────┴───────┘ Max iterations in Expanding/Rolling datatune set to 900. Iterations in SampleDefault are 500. Sampling iterations set to 500 Sampling starts... Sampling finished, printing diagnostics. ##################################################################################### SMC algorithm with jitter kernel MCMC Diagnostics: Sampler finished after 500 iterations with average acceptance ratio of 0.0%. Initial average ℓlikelihood per particle: -1934.497, variance: 457.537 Final average ℓlikelihood per particle: -1569.273, variance: 1.06 Total number of jittering steps: 562. Rejuvenations on average every 1.0 step, every 1.0 steps in first half, every 1.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.783, 0.009, 0.368, 0.69, 0.934]. Quantiles for average number rejuvenation steps: [1.0, 1.0, 1.0, 1.0, 2.0]. Quantiles for ESS: [3.939, 3.994, 3.998, 3.999, 4.0] for 4 chains. ┌───┬───────┬───────┬────────┬────────┬───────┬───────┬───────┬───────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼───────┼───────┼────────┼────────┼───────┼───────┼───────┼───────┼──────────┼──────────┼───────┤ │ μ │ 0.086 │ 0.068 │ 0.003 │ -0.001 │ 0.057 │ 0.083 │ 0.107 │ 0.162 │ 48.63 │ 381.837 │ 1.062 │ │ σ │ 1.082 │ 0.728 │ 0.04 │ 0.949 │ 0.986 │ 1.003 │ 1.021 │ 1.06 │ 775.443 │ 642.105 │ 1.015 │ └───┴───────┴───────┴────────┴────────┴───────┴───────┴───────┴───────┴──────────┴──────────┴───────┘ Max iterations in Expanding/Rolling datatune set to 900. Iterations in SampleDefault are 500. Sampling iterations set to 500 Constructing new sampler... Sampling starts... Sampling finished, printing diagnostics and saving trace. ##################################################################################### SMC algorithm with jitter kernel SMC2Kernel Diagnostics: Sampler finished after 500 iterations with average acceptance ratio of 97.0%. Initial average ℓlikelihood per particle: -158.388, variance: 4.156 Final average ℓlikelihood per particle: -972.338, variance: 1.3 Total number of jittering steps: 89. Rejuvenations on average every 33.333 step, every 20.833 steps in first half, every 83.333 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.336, -0.117, 0.011, 0.168, 0.562]. Quantiles for average number rejuvenation steps: [1.35, 4.0, 6.0, 9.0, 10.0]. Quantiles for ESS: [2.977, 3.426, 3.682, 3.877, 3.988] for 4 chains. ┌────┬────────┬───────┬────────┬───────┬────────┬────────┬───────┬───────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├────┼────────┼───────┼────────┼───────┼────────┼────────┼───────┼───────┼──────────┼──────────┼───────┤ │ μ1 │ -0.323 │ 0.836 │ 0.236 │ -2.22 │ -0.635 │ -0.273 │ 0.262 │ 0.912 │ 10.778 │ 46.267 │ 1.291 │ │ μ2 │ 1.953 │ 0.091 │ 0.014 │ 1.765 │ 1.886 │ 1.945 │ 2.027 │ 2.102 │ 38.335 │ 30.142 │ 1.261 │ │ σ1 │ 2.004 │ 0.497 │ 0.076 │ 1.414 │ 1.79 │ 1.933 │ 2.151 │ 3.089 │ 34.574 │ 33.927 │ 1.082 │ │ σ2 │ 0.985 │ 0.061 │ 0.01 │ 0.839 │ 0.96 │ 0.981 │ 1.028 │ 1.106 │ 31.678 │ 45.277 │ 1.17 │ │ p1 │ 0.136 │ 0.049 │ 0.018 │ 0.057 │ 0.095 │ 0.132 │ 0.177 │ 0.24 │ 8.033 │ 51.341 │ 1.454 │ │ p2 │ 0.864 │ 0.049 │ 0.018 │ 0.76 │ 0.823 │ 0.868 │ 0.905 │ 0.943 │ 8.033 │ 20.781 │ 1.454 │ └────┴────────┴───────┴────────┴───────┴────────┴────────┴───────┴───────┴──────────┴──────────┴───────┘ Max iterations in Expanding/Rolling datatune set to 900. Iterations in SampleDefault are 500. Sampling iterations set to 500 Sampling starts... Sampling finished, printing diagnostics. ##################################################################################### SMC algorithm with jitter kernel SMC2Kernel Diagnostics: Sampler finished after 500 iterations with average acceptance ratio of 98.6%. Initial average ℓlikelihood per particle: -975.086, variance: 1.418 Final average ℓlikelihood per particle: -1587.685, variance: 1.246 Total number of jittering steps: 60. Rejuvenations on average every 71.429 step, every 50.0 steps in first half, every 125.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [0.031, 0.36, 0.454, 0.494, 0.757]. Quantiles for average number rejuvenation steps: [3.6, 8.5, 10.0, 10.0, 10.0]. Quantiles for ESS: [3.077, 3.353, 3.653, 3.805, 3.976] for 4 chains. ┌────┬────────┬───────┬────────┬────────┬────────┬────────┬────────┬───────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├────┼────────┼───────┼────────┼────────┼────────┼────────┼────────┼───────┼──────────┼──────────┼───────┤ │ μ1 │ -0.075 │ 0.117 │ 0.028 │ -0.286 │ -0.127 │ -0.073 │ -0.041 │ 0.21 │ 19.997 │ 21.871 │ 1.166 │ │ μ2 │ 0.804 │ 0.537 │ 0.22 │ -0.221 │ 0.289 │ 0.776 │ 1.25 │ 1.889 │ 5.986 │ 8.815 │ 1.809 │ │ σ1 │ 0.984 │ 0.145 │ 0.021 │ 0.834 │ 0.91 │ 0.96 │ 1.043 │ 1.079 │ 9.369 │ 38.388 │ 1.376 │ │ σ2 │ 0.94 │ 0.087 │ 0.022 │ 0.817 │ 0.851 │ 0.925 │ 0.994 │ 1.096 │ 14.796 │ NaN │ 1.294 │ │ p1 │ 0.782 │ 0.125 │ 0.027 │ 0.55 │ 0.738 │ 0.802 │ 0.861 │ 0.914 │ 9.67 │ NaN │ 1.333 │ │ p2 │ 0.218 │ 0.125 │ 0.027 │ 0.086 │ 0.139 │ 0.198 │ 0.262 │ 0.45 │ 9.67 │ 10.794 │ 1.333 │ └────┴────────┴───────┴────────┴────────┴────────┴────────┴────────┴───────┴──────────┴──────────┴───────┘ Max iterations in Expanding/Rolling datatune set to 900. Iterations in SampleDefault are 500. Sampling iterations set to 500 Constructing new sampler... Sampling starts... Sampling finished, printing diagnostics and saving trace. ##################################################################################### ########################################## Chain 1: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 500 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -111.004, Avg. final ℓposterior: -2253.041. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 15.252 (31) number of steps and depth of 3.344 (5). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 2: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 500 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -110.669, Avg. final ℓposterior: -2253.044. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 15.624 (19) number of steps and depth of 3.356 (4). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 3: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 500 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -111.115, Avg. final ℓposterior: -2253.771. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 15.62 (15) number of steps and depth of 3.336 (4). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 4: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 500 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -110.614, Avg. final ℓposterior: -2253.026. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 17.624 (7) number of steps and depth of 3.468 (3). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ┌───┬────────┬───────┬────────┬────────┬────────┬────────┬────────┬────────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼────────┼───────┼────────┼────────┼────────┼────────┼────────┼────────┼──────────┼──────────┼───────┤ │ μ │ 0.225 │ 0.541 │ 0.032 │ -0.841 │ -0.115 │ 0.219 │ 0.553 │ 1.329 │ 289.952 │ 381.955 │ 1.03 │ │ σ │ 10.315 │ 0.534 │ 0.053 │ 9.025 │ 10.034 │ 10.331 │ 10.658 │ 11.284 │ 120.301 │ 80.088 │ 1.039 │ └───┴────────┴───────┴────────┴────────┴────────┴────────┴────────┴────────┴──────────┴──────────┴───────┘ Max iterations in Expanding/Rolling datatune set to 400. Iterations in SampleDefault are 500. Sampling iterations set to 400 Sampling starts... Sampling finished, printing diagnostics. ##################################################################################### ########################################## Chain 1: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 400 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -652.4, Avg. final ℓposterior: -3735.876. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 15.35 (15) number of steps and depth of 3.37 (4). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 2: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 400 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -652.592, Avg. final ℓposterior: -3735.681. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 17.895 (19) number of steps and depth of 3.52 (4). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 3: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 400 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -652.279, Avg. final ℓposterior: -3737.594. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 17.1 (15) number of steps and depth of 3.535 (3). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 4: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 400 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -652.692, Avg. final ℓposterior: -3737.473. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 17.52 (15) number of steps and depth of 3.475 (4). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ┌───┬────────┬───────┬────────┬────────┬────────┬────────┬────────┬────────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼────────┼───────┼────────┼────────┼────────┼────────┼────────┼────────┼──────────┼──────────┼───────┤ │ μ │ 0.143 │ 0.348 │ 0.024 │ -0.552 │ -0.082 │ 0.146 │ 0.362 │ 0.873 │ 211.032 │ 238.41 │ 1.01 │ │ σ │ 10.091 │ 0.284 │ 0.039 │ 9.571 │ 9.899 │ 10.073 │ 10.269 │ 10.693 │ 55.002 │ 534.63 │ 1.057 │ └───┴────────┴───────┴────────┴────────┴────────┴────────┴────────┴────────┴──────────┴──────────┴───────┘ Max iterations in Expanding/Rolling datatune set to 900. Iterations in SampleDefault are 500. Sampling iterations set to 500 Constructing new sampler... Sampling starts... Sampling finished, printing diagnostics and saving trace. ##################################################################################### SMC algorithm with jitter kernel MCMC Diagnostics: Sampler finished after 500 iterations with average acceptance ratio of 0.0%. Initial average ℓlikelihood per particle: -111.414, variance: 0.028 Final average ℓlikelihood per particle: -2255.928, variance: 0.204 Total number of jittering steps: 533. Rejuvenations on average every 1.0 step, every 1.0 steps in first half, every 1.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.601, -0.018, 0.293, 0.659, 0.94]. Quantiles for average number rejuvenation steps: [1.0, 1.0, 1.0, 1.0, 2.0]. Quantiles for ESS: [3.896, 3.988, 3.995, 3.998, 4.0] for 4 chains. ┌───┬────────┬───────┬────────┬───────┬────────┬────────┬────────┬────────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼────────┼───────┼────────┼───────┼────────┼────────┼────────┼────────┼──────────┼──────────┼───────┤ │ μ │ 0.204 │ 0.559 │ 0.04 │ -0.88 │ -0.169 │ 0.186 │ 0.559 │ 1.324 │ 184.205 │ 426.84 │ 1.023 │ │ σ │ 10.288 │ 0.529 │ 0.05 │ 9.143 │ 9.997 │ 10.307 │ 10.607 │ 11.263 │ 123.353 │ 93.784 │ 1.029 │ └───┴────────┴───────┴────────┴───────┴────────┴────────┴────────┴────────┴──────────┴──────────┴───────┘ Max iterations in Expanding/Rolling datatune set to 900. Iterations in SampleDefault are 500. Sampling iterations set to 500 Sampling starts... Sampling finished, printing diagnostics. ##################################################################################### SMC algorithm with jitter kernel MCMC Diagnostics: Sampler finished after 500 iterations with average acceptance ratio of 0.0%. Initial average ℓlikelihood per particle: -553.326, variance: 128.556 Final average ℓlikelihood per particle: -1560.208, variance: 0.473 Total number of jittering steps: 651. Rejuvenations on average every 1.0 step, every 1.0 steps in first half, every 1.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.594, -0.001, 0.389, 0.701, 0.945]. Quantiles for average number rejuvenation steps: [1.0, 1.0, 1.0, 1.0, 4.0]. Quantiles for ESS: [3.956, 3.996, 3.998, 3.999, 4.0] for 4 chains. ┌───┬───────┬───────┬────────┬────────┬────────┬───────┬───────┬───────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼───────┼───────┼────────┼────────┼────────┼───────┼───────┼───────┼──────────┼──────────┼───────┤ │ μ │ 0.021 │ 0.066 │ 0.002 │ -0.052 │ -0.002 │ 0.023 │ 0.046 │ 0.09 │ 167.631 │ 456.364 │ 1.038 │ │ σ │ 1.076 │ 0.681 │ 0.039 │ 0.956 │ 0.989 │ 1.008 │ 1.031 │ 1.099 │ 14.676 │ 106.854 │ 1.187 │ └───┴───────┴───────┴────────┴────────┴────────┴───────┴───────┴───────┴──────────┴──────────┴───────┘ Max iterations in Expanding/Rolling datatune set to 900. Iterations in SampleDefault are 500. Sampling iterations set to 500 Constructing new sampler... Sampling starts... Sampling finished, printing diagnostics and saving trace. ##################################################################################### SMC algorithm with jitter kernel SMC2Kernel Diagnostics: Sampler finished after 500 iterations with average acceptance ratio of 96.8%. Initial average ℓlikelihood per particle: -45.835, variance: 0.188 Final average ℓlikelihood per particle: -971.145, variance: 1.644 Total number of jittering steps: 93. Rejuvenations on average every 31.25 step, every 19.231 steps in first half, every 83.333 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.217, -0.093, 0.029, 0.249, 0.572]. Quantiles for average number rejuvenation steps: [1.375, 3.75, 5.5, 8.5, 10.0]. Quantiles for ESS: [2.984, 3.458, 3.66, 3.824, 3.992] for 4 chains. ┌────┬────────┬───────┬────────┬────────┬────────┬────────┬────────┬───────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├────┼────────┼───────┼────────┼────────┼────────┼────────┼────────┼───────┼──────────┼──────────┼───────┤ │ μ1 │ -0.696 │ 0.882 │ 0.215 │ -2.821 │ -1.092 │ -0.778 │ -0.028 │ 0.841 │ 23.115 │ 12.23 │ 1.312 │ │ μ2 │ 1.924 │ 0.065 │ 0.012 │ 1.816 │ 1.874 │ 1.908 │ 1.962 │ 2.083 │ 30.941 │ 52.577 │ 1.084 │ │ σ1 │ 1.889 │ 0.645 │ 0.181 │ 1.054 │ 1.485 │ 1.768 │ 2.044 │ 3.044 │ 7.806 │ 11.605 │ 1.452 │ │ σ2 │ 0.992 │ 0.069 │ 0.017 │ 0.874 │ 0.939 │ 0.996 │ 1.02 │ 1.15 │ 13.686 │ NaN │ 1.231 │ │ p1 │ 0.109 │ 0.036 │ 0.009 │ 0.053 │ 0.085 │ 0.111 │ 0.121 │ 0.189 │ 16.339 │ 18.177 │ 1.223 │ │ p2 │ 0.891 │ 0.036 │ 0.009 │ 0.811 │ 0.879 │ 0.889 │ 0.915 │ 0.947 │ 16.339 │ 56.762 │ 1.223 │ └────┴────────┴───────┴────────┴────────┴────────┴────────┴────────┴───────┴──────────┴──────────┴───────┘ Max iterations in Expanding/Rolling datatune set to 900. Iterations in SampleDefault are 500. Sampling iterations set to 500 Sampling starts... Sampling finished, printing diagnostics. ##################################################################################### SMC algorithm with jitter kernel SMC2Kernel Diagnostics: Sampler finished after 500 iterations with average acceptance ratio of 98.2%. Initial average ℓlikelihood per particle: -281.856, variance: 0.212 Final average ℓlikelihood per particle: -1560.447, variance: 2.922 Total number of jittering steps: 70. Rejuvenations on average every 55.556 step, every 35.714 steps in first half, every 125.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.343, -0.108, 0.617, 0.929, 0.946]. Quantiles for average number rejuvenation steps: [1.4, 6.0, 10.0, 10.0, 10.0]. Quantiles for ESS: [3.047, 3.387, 3.676, 3.874, 3.991] for 4 chains. ┌────┬────────┬───────┬────────┬────────┬────────┬────────┬────────┬────────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├────┼────────┼───────┼────────┼────────┼────────┼────────┼────────┼────────┼──────────┼──────────┼───────┤ │ μ1 │ -0.481 │ 0.142 │ 0.059 │ -0.679 │ -0.633 │ -0.445 │ -0.351 │ -0.225 │ 6.428 │ 17.865 │ 1.776 │ │ μ2 │ 0.796 │ 0.218 │ 0.083 │ 0.478 │ 0.609 │ 0.804 │ 0.967 │ 1.164 │ 7.283 │ 22.297 │ 1.524 │ │ σ1 │ 0.777 │ 0.075 │ 0.02 │ 0.687 │ 0.714 │ 0.78 │ 0.835 │ 0.905 │ 10.08 │ 19.35 │ 1.389 │ │ σ2 │ 0.757 │ 0.077 │ 0.028 │ 0.625 │ 0.72 │ 0.741 │ 0.795 │ 0.921 │ 6.228 │ 9.312 │ 1.777 │ │ p1 │ 0.599 │ 0.122 │ 0.049 │ 0.431 │ 0.474 │ 0.645 │ 0.716 │ 0.788 │ 6.971 │ 17.614 │ 1.645 │ │ p2 │ 0.401 │ 0.122 │ 0.049 │ 0.212 │ 0.284 │ 0.355 │ 0.526 │ 0.569 │ 6.971 │ 10.202 │ 1.645 │ └────┴────────┴───────┴────────┴────────┴────────┴────────┴────────┴────────┴──────────┴──────────┴───────┘ Max iterations in Expanding/Rolling datatune set to 900. Iterations in SampleDefault are 500. Sampling iterations set to 500 Constructing new sampler... Sampling starts... Sampling finished, printing diagnostics and saving trace. ##################################################################################### ########################################## Chain 1: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 500 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -191.383, Avg. final ℓposterior: -1126.935. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 17.812 (15) number of steps and depth of 3.52 (4). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 2: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 500 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -191.484, Avg. final ℓposterior: -1126.896. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 16.876 (7) number of steps and depth of 3.486 (2). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 3: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 500 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -191.351, Avg. final ℓposterior: -1127.348. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 16.784 (7) number of steps and depth of 3.446 (3). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 4: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 500 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -194.109, Avg. final ℓposterior: -1126.555. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 17.224 (31) number of steps and depth of 3.462 (4). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ┌───┬────────┬───────┬────────┬────────┬────────┬────────┬────────┬────────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼────────┼───────┼────────┼────────┼────────┼────────┼────────┼────────┼──────────┼──────────┼───────┤ │ μ │ 0.209 │ 0.721 │ 0.05 │ -1.161 │ -0.281 │ 0.207 │ 0.698 │ 1.591 │ 212.469 │ 554.496 │ 1.013 │ │ σ │ 10.351 │ 0.646 │ 0.055 │ 8.955 │ 9.98 │ 10.359 │ 10.747 │ 11.585 │ 154.01 │ 84.93 │ 1.033 │ └───┴────────┴───────┴────────┴────────┴────────┴────────┴────────┴────────┴──────────┴──────────┴───────┘ Max iterations in Expanding/Rolling datatune set to 400. Iterations in SampleDefault are 500. Sampling iterations set to 400 Sampling starts... Sampling finished, printing diagnostics. ##################################################################################### ########################################## Chain 1: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 400 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1128.317, Avg. final ℓposterior: -1868.94. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 16.14 (31) number of steps and depth of 3.455 (4). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 2: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 400 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1129.522, Avg. final ℓposterior: -1873.406. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 14.2 (15) number of steps and depth of 3.305 (4). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 3: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 400 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1128.321, Avg. final ℓposterior: -1868.269. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 15.51 (31) number of steps and depth of 3.402 (4). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 4: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 400 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1128.285, Avg. final ℓposterior: -1868.842. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 15.695 (15) number of steps and depth of 3.402 (3). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ┌───┬────────┬───────┬────────┬────────┬────────┬───────┬────────┬────────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼────────┼───────┼────────┼────────┼────────┼───────┼────────┼────────┼──────────┼──────────┼───────┤ │ μ │ 0.152 │ 0.491 │ 0.027 │ -0.776 │ -0.177 │ 0.169 │ 0.462 │ 1.108 │ 353.851 │ 416.429 │ 1.015 │ │ σ │ 10.104 │ 0.373 │ 0.029 │ 9.4 │ 9.853 │ 10.08 │ 10.347 │ 10.863 │ 190.712 │ 772.07 │ 1.027 │ └───┴────────┴───────┴────────┴────────┴────────┴───────┴────────┴────────┴──────────┴──────────┴───────┘ Max iterations in Expanding/Rolling datatune set to 900. Iterations in SampleDefault are 500. Sampling iterations set to 500 Constructing new sampler... Sampling starts... Sampling finished, printing diagnostics and saving trace. ##################################################################################### SMC algorithm with jitter kernel MCMC Diagnostics: Sampler finished after 500 iterations with average acceptance ratio of 0.0%. Initial average ℓlikelihood per particle: -193.287, variance: 0.111 Final average ℓlikelihood per particle: -1128.993, variance: 0.646 Total number of jittering steps: 541. Rejuvenations on average every 1.0 step, every 1.0 steps in first half, every 1.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.558, 0.03, 0.371, 0.664, 0.939]. Quantiles for average number rejuvenation steps: [1.0, 1.0, 1.0, 1.0, 2.0]. Quantiles for ESS: [3.934, 3.994, 3.998, 3.999, 4.0] for 4 chains. ┌───┬───────┬───────┬────────┬────────┬────────┬────────┬───────┬────────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼───────┼───────┼────────┼────────┼────────┼────────┼───────┼────────┼──────────┼──────────┼───────┤ │ μ │ 0.154 │ 0.747 │ 0.043 │ -1.452 │ -0.309 │ 0.197 │ 0.668 │ 1.54 │ 307.26 │ 407.431 │ 1.026 │ │ σ │ 10.36 │ 0.67 │ 0.051 │ 8.771 │ 10.005 │ 10.378 │ 10.76 │ 11.636 │ 199.001 │ 98.323 │ 1.037 │ └───┴───────┴───────┴────────┴────────┴────────┴────────┴───────┴────────┴──────────┴──────────┴───────┘ Max iterations in Expanding/Rolling datatune set to 900. Iterations in SampleDefault are 500. Sampling iterations set to 500 Sampling starts... Sampling finished, printing diagnostics. ##################################################################################### SMC algorithm with jitter kernel MCMC Diagnostics: Sampler finished after 500 iterations with average acceptance ratio of 0.0%. Initial average ℓlikelihood per particle: -802.039, variance: 35301.894 Final average ℓlikelihood per particle: -774.329, variance: 2.253 Total number of jittering steps: 558. Rejuvenations on average every 1.0 step, every 1.0 steps in first half, every 1.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.628, -0.016, 0.341, 0.664, 0.908]. Quantiles for average number rejuvenation steps: [1.0, 1.0, 1.0, 1.0, 2.0]. Quantiles for ESS: [3.97, 3.997, 3.999, 3.999, 4.0] for 4 chains. ┌───┬───────┬───────┬────────┬────────┬────────┬───────┬───────┬───────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼───────┼───────┼────────┼────────┼────────┼───────┼───────┼───────┼──────────┼──────────┼───────┤ │ μ │ 0.023 │ 0.057 │ 0.003 │ -0.074 │ -0.013 │ 0.021 │ 0.057 │ 0.125 │ 252.679 │ 627.963 │ 1.026 │ │ σ │ 1.0 │ 0.291 │ 0.009 │ 0.909 │ 0.96 │ 0.984 │ 1.008 │ 1.069 │ 596.68 │ 399.207 │ 1.018 │ └───┴───────┴───────┴────────┴────────┴────────┴───────┴───────┴───────┴──────────┴──────────┴───────┘ Max iterations in Expanding/Rolling datatune set to 900. Iterations in SampleDefault are 500. Sampling iterations set to 500 Constructing new sampler... Sampling starts... Sampling finished, printing diagnostics and saving trace. ##################################################################################### SMC algorithm with jitter kernel SMC2Kernel Diagnostics: Sampler finished after 500 iterations with average acceptance ratio of 98.6%. Initial average ℓlikelihood per particle: -82.632, variance: 21.676 Final average ℓlikelihood per particle: -486.137, variance: 1.118 Total number of jittering steps: 49. Rejuvenations on average every 71.429 step, every 41.667 steps in first half, every 250.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.283, -0.11, 0.148, 0.181, 0.228]. Quantiles for average number rejuvenation steps: [5.0, 5.5, 6.0, 8.5, 10.0]. Quantiles for ESS: [3.074, 3.5, 3.706, 3.868, 3.994] for 4 chains. ┌────┬───────┬───────┬────────┬────────┬────────┬────────┬────────┬───────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├────┼───────┼───────┼────────┼────────┼────────┼────────┼────────┼───────┼──────────┼──────────┼───────┤ │ μ1 │ -0.95 │ 1.292 │ 0.346 │ -3.774 │ -1.293 │ -0.809 │ -0.049 │ 0.468 │ 12.873 │ 21.982 │ 1.448 │ │ μ2 │ 1.926 │ 0.1 │ 0.029 │ 1.622 │ 1.896 │ 1.945 │ 1.98 │ 2.038 │ 14.934 │ 18.859 │ 1.437 │ │ σ1 │ 2.023 │ 0.987 │ 0.191 │ 0.994 │ 1.511 │ 1.759 │ 2.103 │ 5.885 │ 30.544 │ 38.903 │ 1.434 │ │ σ2 │ 0.996 │ 0.075 │ 0.011 │ 0.867 │ 0.952 │ 0.982 │ 1.01 │ 1.144 │ 39.974 │ 36.13 │ 1.391 │ │ p1 │ 0.103 │ 0.045 │ 0.015 │ 0.016 │ 0.063 │ 0.111 │ 0.128 │ 0.188 │ 10.048 │ 38.32 │ 1.356 │ │ p2 │ 0.897 │ 0.045 │ 0.015 │ 0.812 │ 0.872 │ 0.889 │ 0.937 │ 0.984 │ 10.048 │ 14.412 │ 1.356 │ └────┴───────┴───────┴────────┴────────┴────────┴────────┴────────┴───────┴──────────┴──────────┴───────┘ Max iterations in Expanding/Rolling datatune set to 900. Iterations in SampleDefault are 500. Sampling iterations set to 500 Sampling starts... Sampling finished, printing diagnostics. ##################################################################################### SMC algorithm with jitter kernel SMC2Kernel Diagnostics: Sampler finished after 500 iterations with average acceptance ratio of 98.4%. Initial average ℓlikelihood per particle: -486.785, variance: 1.106 Final average ℓlikelihood per particle: -786.107, variance: 3.216 Total number of jittering steps: 80. Rejuvenations on average every 62.5 step, every 35.714 steps in first half, every 250.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [0.108, 0.18, 0.743, 0.892, 0.995]. Quantiles for average number rejuvenation steps: [10.0, 10.0, 10.0, 10.0, 10.0]. Quantiles for ESS: [3.037, 3.42, 3.7, 3.936, 3.995] for 4 chains. ┌────┬────────┬───────┬────────┬───────┬────────┬────────┬────────┬───────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├────┼────────┼───────┼────────┼───────┼────────┼────────┼────────┼───────┼──────────┼──────────┼───────┤ │ μ1 │ -0.147 │ 0.192 │ 0.045 │ -0.69 │ -0.186 │ -0.127 │ -0.081 │ 0.343 │ 11.985 │ 14.395 │ 1.239 │ │ μ2 │ 1.303 │ 0.524 │ 0.22 │ 0.439 │ 0.891 │ 1.61 │ 1.749 │ 1.98 │ 7.133 │ NaN │ 1.67 │ │ σ1 │ 1.043 │ 0.306 │ 0.055 │ 0.755 │ 0.917 │ 0.943 │ 1.009 │ 2.103 │ 32.222 │ 17.017 │ 1.563 │ │ σ2 │ 1.155 │ 0.189 │ 0.041 │ 0.781 │ 0.982 │ 1.248 │ 1.268 │ 1.442 │ 19.344 │ 10.675 │ 1.179 │ │ p1 │ 0.715 │ 0.27 │ 0.086 │ 0.111 │ 0.692 │ 0.799 │ 0.922 │ 0.969 │ 7.477 │ NaN │ 1.493 │ │ p2 │ 0.285 │ 0.27 │ 0.086 │ 0.031 │ 0.078 │ 0.201 │ 0.308 │ 0.889 │ 7.477 │ 9.362 │ 1.493 │ └────┴────────┴───────┴────────┴───────┴────────┴────────┴────────┴───────┴──────────┴──────────┴───────┘ Max iterations in Expanding/Rolling datatune set to 900. Iterations in SampleDefault are 500. Sampling iterations set to 500 Constructing new sampler... Sampling starts... Sampling finished, printing diagnostics and saving trace. ##################################################################################### ########################################## Chain 1: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 500 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -191.383, Avg. final ℓposterior: -1563.149. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 16.924 (31) number of steps and depth of 3.452 (4). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 2: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 500 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -192.231, Avg. final ℓposterior: -1561.608. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 13.96 (31) number of steps and depth of 3.26 (4). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 3: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 500 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -196.016, Avg. final ℓposterior: -1562.279. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 15.8 (23) number of steps and depth of 3.38 (4). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 4: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 500 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -191.59, Avg. final ℓposterior: -1561.289. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 14.896 (23) number of steps and depth of 3.316 (4). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ┌───┬────────┬───────┬────────┬────────┬────────┬────────┬────────┬────────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼────────┼───────┼────────┼────────┼────────┼────────┼────────┼────────┼──────────┼──────────┼───────┤ │ μ │ 0.229 │ 0.697 │ 0.033 │ -1.152 │ -0.198 │ 0.247 │ 0.65 │ 1.6 │ 444.527 │ 496.32 │ 1.044 │ │ σ │ 10.337 │ 0.633 │ 0.055 │ 8.859 │ 10.0 │ 10.338 │ 10.713 │ 11.568 │ 156.273 │ 86.143 │ 1.054 │ └───┴────────┴───────┴────────┴────────┴────────┴────────┴────────┴────────┴──────────┴──────────┴───────┘ Max iterations in Expanding/Rolling datatune set to 400. Iterations in SampleDefault are 500. Sampling iterations set to 400 Sampling starts... Sampling finished, printing diagnostics. ##################################################################################### ########################################## Chain 1: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 400 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1564.529, Avg. final ℓposterior: -3105.465. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 14.88 (7) number of steps and depth of 3.392 (2). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 2: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 400 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1564.307, Avg. final ℓposterior: -3106.458. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 14.515 (15) number of steps and depth of 3.332 (4). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 3: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 400 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1564.512, Avg. final ℓposterior: -3107.165. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 15.745 (15) number of steps and depth of 3.42 (4). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ########################################## Chain 4: MCMC Diagnostics: ### NUTS parameter target: (:μ, :σ) Sampler finished after 400 iterations with acceptance rates of 100.0%. Avg. initial ℓposterior: -1564.812, Avg. final ℓposterior: -3105.582. NUTS sampler had 0 divergent transitions. Average (final) stepsize of 0.1 (0.1) with 14.33 (15) number of steps and depth of 3.332 (3). Divergences in: Warmup: 0, Adaptionˢˡᵒʷ: 0, Adaptionᶠᵃˢᵗ: 0, Exploration: 0. ┌───┬────────┬───────┬────────┬────────┬────────┬────────┬────────┬────────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼────────┼───────┼────────┼────────┼────────┼────────┼────────┼────────┼──────────┼──────────┼───────┤ │ μ │ 0.146 │ 0.427 │ 0.026 │ -0.762 │ -0.116 │ 0.148 │ 0.432 │ 0.97 │ 283.49 │ 316.048 │ 1.017 │ │ σ │ 10.086 │ 0.296 │ 0.026 │ 9.557 │ 9.889 │ 10.074 │ 10.281 │ 10.709 │ 145.866 │ 495.055 │ 1.038 │ └───┴────────┴───────┴────────┴────────┴────────┴────────┴────────┴────────┴──────────┴──────────┴───────┘ Max iterations in Expanding/Rolling datatune set to 900. Iterations in SampleDefault are 500. Sampling iterations set to 500 Constructing new sampler... Sampling starts... Sampling finished, printing diagnostics and saving trace. ##################################################################################### SMC algorithm with jitter kernel MCMC Diagnostics: Sampler finished after 500 iterations with average acceptance ratio of 0.0%. Initial average ℓlikelihood per particle: -193.907, variance: 0.947 Final average ℓlikelihood per particle: -1564.105, variance: 0.929 Total number of jittering steps: 529. Rejuvenations on average every 1.0 step, every 1.0 steps in first half, every 1.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.624, -0.005, 0.317, 0.613, 0.929]. Quantiles for average number rejuvenation steps: [1.0, 1.0, 1.0, 1.0, 2.0]. Quantiles for ESS: [3.933, 3.994, 3.997, 3.999, 4.0] for 4 chains. ┌───┬────────┬───────┬────────┬────────┬────────┬───────┬────────┬───────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼────────┼───────┼────────┼────────┼────────┼───────┼────────┼───────┼──────────┼──────────┼───────┤ │ μ │ 0.175 │ 0.685 │ 0.038 │ -1.339 │ -0.246 │ 0.207 │ 0.629 │ 1.398 │ 366.521 │ 301.923 │ 1.031 │ │ σ │ 10.319 │ 0.634 │ 0.049 │ 8.977 │ 9.974 │ 10.34 │ 10.689 │ 11.57 │ 176.398 │ 88.909 │ 1.047 │ └───┴────────┴───────┴────────┴────────┴────────┴───────┴────────┴───────┴──────────┴──────────┴───────┘ Max iterations in Expanding/Rolling datatune set to 900. Iterations in SampleDefault are 500. Sampling iterations set to 500 Sampling starts... Sampling finished, printing diagnostics. ##################################################################################### SMC algorithm with jitter kernel MCMC Diagnostics: Sampler finished after 500 iterations with average acceptance ratio of 0.0%. Initial average ℓlikelihood per particle: -1274.41, variance: 8167.121 Final average ℓlikelihood per particle: -1361.256, variance: 0.883 Total number of jittering steps: 629. Rejuvenations on average every 1.0 step, every 1.0 steps in first half, every 1.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.692, 0.042, 0.413, 0.73, 0.96]. Quantiles for average number rejuvenation steps: [1.0, 1.0, 1.0, 1.0, 3.0]. Quantiles for ESS: [3.948, 3.996, 3.998, 3.999, 4.0] for 4 chains. ┌───┬────────┬───────┬────────┬────────┬────────┬────────┬────────┬───────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├───┼────────┼───────┼────────┼────────┼────────┼────────┼────────┼───────┼──────────┼──────────┼───────┤ │ μ │ -0.036 │ 0.05 │ 0.002 │ -0.121 │ -0.063 │ -0.035 │ -0.008 │ 0.041 │ 199.72 │ 640.749 │ 1.04 │ │ σ │ 1.045 │ 0.364 │ 0.012 │ 0.966 │ 1.003 │ 1.023 │ 1.043 │ 1.094 │ 214.22 │ 371.196 │ 1.026 │ └───┴────────┴───────┴────────┴────────┴────────┴────────┴────────┴───────┴──────────┴──────────┴───────┘ Max iterations in Expanding/Rolling datatune set to 900. Iterations in SampleDefault are 500. Sampling iterations set to 500 Constructing new sampler... Sampling starts... Sampling finished, printing diagnostics and saving trace. ##################################################################################### SMC algorithm with jitter kernel SMC2Kernel Diagnostics: Sampler finished after 500 iterations with average acceptance ratio of 98.2%. Initial average ℓlikelihood per particle: -82.927, variance: 14.317 Final average ℓlikelihood per particle: -673.735, variance: 5.958 Total number of jittering steps: 55. Rejuvenations on average every 55.556 step, every 35.714 steps in first half, every 125.0 steps in second half. Quantiles for average rejuvenation correlation of parameter: [-0.078, 0.012, 0.103, 0.235, 0.835]. Quantiles for average number rejuvenation steps: [2.0, 3.0, 5.0, 10.0, 10.0]. Quantiles for ESS: [3.031, 3.37, 3.716, 3.888, 3.996] for 4 chains. ┌────┬────────┬───────┬────────┬────────┬────────┬────────┬───────┬───────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├────┼────────┼───────┼────────┼────────┼────────┼────────┼───────┼───────┼──────────┼──────────┼───────┤ │ μ1 │ -1.637 │ 1.496 │ 0.464 │ -6.448 │ -2.345 │ -1.586 │ -0.46 │ 0.623 │ 9.86 │ 25.978 │ 1.358 │ │ μ2 │ 1.913 │ 0.109 │ 0.03 │ 1.644 │ 1.829 │ 1.929 │ 2.001 │ 2.076 │ 12.256 │ 42.188 │ 1.32 │ │ σ1 │ 2.069 │ 1.159 │ 0.244 │ 0.972 │ 1.417 │ 1.718 │ 2.101 │ 5.849 │ 25.203 │ 33.702 │ 1.142 │ │ σ2 │ 1.019 │ 0.079 │ 0.013 │ 0.916 │ 0.968 │ 1.013 │ 1.044 │ 1.258 │ 29.94 │ 22.405 │ 1.137 │ │ p1 │ 0.084 │ 0.039 │ 0.012 │ 0.013 │ 0.059 │ 0.087 │ 0.116 │ 0.156 │ 12.647 │ 17.486 │ 1.355 │ │ p2 │ 0.916 │ 0.039 │ 0.012 │ 0.844 │ 0.884 │ 0.913 │ 0.941 │ 0.987 │ 12.647 │ 22.574 │ 1.355 │ └────┴────────┴───────┴────────┴────────┴────────┴────────┴───────┴───────┴──────────┴──────────┴───────┘ Max iterations in Expanding/Rolling datatune set to 900. Iterations in SampleDefault are 500. Sampling iterations set to 500 Sampling starts... Sampling finished, printing diagnostics. ##################################################################################### SMC algorithm with jitter kernel SMC2Kernel Diagnostics: Sampler finished after 500 iterations with average acceptance ratio of 98.6%. Initial average ℓlikelihood per particle: -675.926, variance: 6.08 Final average ℓlikelihood per particle: -1342.585, variance: 3.101 Total number of jittering steps: 59. Rejuvenations on average every 71.429 step, every 35.714 steps in first half, every Inf steps in second half. Quantiles for average rejuvenation correlation of parameter: [0.265, 0.477, 0.8, 0.898, 0.997]. Quantiles for average number rejuvenation steps: [2.05, 9.0, 10.0, 10.0, 10.0]. Quantiles for ESS: [3.081, 3.427, 3.686, 3.821, 3.985] for 4 chains. ┌────┬────────┬───────┬────────┬────────┬────────┬────────┬────────┬───────┬──────────┬──────────┬───────┐ │ │ Mean │ MCSE │ StdDev │ Q2.5 │ Q25.0 │ Q50.0 │ Q75.0 │ Q97.5 │ ESS_bulk │ ESS_tail │ Rhat │ ├────┼────────┼───────┼────────┼────────┼────────┼────────┼────────┼───────┼──────────┼──────────┼───────┤ │ μ1 │ -0.138 │ 0.312 │ 0.064 │ -0.547 │ -0.144 │ -0.058 │ -0.042 │ 0.05 │ 5.817 │ NaN │ 1.855 │ │ μ2 │ 1.571 │ 0.169 │ 0.049 │ 1.457 │ 1.471 │ 1.485 │ 1.534 │ 2.066 │ 5.611 │ 4.208 │ 1.926 │ │ σ1 │ 1.023 │ 0.215 │ 0.037 │ 0.842 │ 0.954 │ 0.96 │ 0.966 │ 1.912 │ 12.161 │ 10.779 │ 1.839 │ │ σ2 │ 1.243 │ 0.129 │ 0.05 │ 0.995 │ 1.264 │ 1.296 │ 1.318 │ 1.37 │ 6.035 │ NaN │ 1.789 │ │ p1 │ 0.854 │ 0.261 │ 0.058 │ 0.092 │ 0.944 │ 0.957 │ 0.971 │ 0.977 │ 5.744 │ NaN │ 1.882 │ │ p2 │ 0.146 │ 0.261 │ 0.058 │ 0.023 │ 0.029 │ 0.043 │ 0.056 │ 0.908 │ 5.744 │ 4.208 │ 1.882 │ └────┴────────┴───────┴────────┴────────┴────────┴────────┴────────┴───────┴──────────┴──────────┴───────┘ ┌ Warning: The call to compilecache failed to create a usable precompiled cache file for Optim [429524aa-4258-5aef-a3af-852621145aeb] │ exception = Required dependency Base.PkgId(Base.UUID("4e289a0a-7415-4d19-859d-a7e5c4648b56"), "EnumX") failed to load from a cache file. └ @ Base loading.jl:2891 ERROR: LoadError: Precompiled image Base.PkgId(Base.UUID("429524aa-4258-5aef-a3af-852621145aeb"), "Optim") not available with flags CacheFlags(; use_pkgimages=false, debug_level=1, check_bounds=0, inline=true, opt_level=0) Stacktrace:  [1] error(s::String)  @ Base ./error.jl:44  [2] __require_prelocked(pkg::Base.PkgId, env::String)  @ Base ./loading.jl:2813  [3] _require_prelocked(uuidkey::Base.PkgId, env::String)  @ Base ./loading.jl:2665  [4] macro expansion  @ ./loading.jl:2593 [inlined]  [5] macro expansion  @ ./lock.jl:376 [inlined]  [6] __require(into::Module, mod::Symbol)  @ Base ./loading.jl:2557  [7] require  @ ./loading.jl:2533 [inlined]  [8] eval_import_path  @ ./module.jl:36 [inlined]  [9] eval_import_path_all(at::Module, path::Expr, keyword::String)  @ Base ./module.jl:60  [10] _eval_using  @ ./module.jl:137 [inlined]  [11] _eval_using(to::Module, path::Expr)  @ Base ./module.jl:137  [12] top-level scope  @ ~/.julia/packages/BaytesOptim/VHjJJ/ext/BaytesOptimOptimExt.jl:6  [13] include(mod::Module, _path::String)  @ Base ./Base.jl:309  [14] include_package_for_output(pkg::Base.PkgId, input::String, syntax_version::VersionNumber, depot_path::Vector{String}, dl_load_path::Vector{String}, load_path::Vector{String}, concrete_deps::Vector{Pair{Base.PkgId, UInt128}}, source::Nothing)  @ Base ./loading.jl:3250  [15] top-level scope  @ stdin:5  [16] eval(m::Module, e::Any)  @ Core ./boot.jl:489  [17] include_string(mapexpr::typeof(identity), mod::Module, code::String, filename::String)  @ Base ./loading.jl:3092  [18] include_string  @ ./loading.jl:3102 [inlined]  [19] exec_options(opts::Base.JLOptions)  @ Base ./client.jl:342  [20] _start()  @ Base ./client.jl:577 in expression starting at /home/pkgeval/.julia/packages/BaytesOptim/VHjJJ/ext/BaytesOptimOptimExt.jl:1 in expression starting at stdin:5 1 dependency had output during precompilation: ┌ BaytesOptim → BaytesOptimOptimExt │ [Output was shown above] └ ┌ Error: Error during loading of extension BaytesOptimOptimExt of BaytesOptim, use `Base.retry_load_extensions()` to retry. │ exception = │ 1-element ExceptionStack: │ The following 1 package failed to precompile: │ │ BaytesOptimOptimExt │ Failed to precompile BaytesOptimOptimExt [75790c33-b7c8-57bf-8222-3af08d1c00b4] to "/home/pkgeval/.julia/compiled/v1.14/BaytesOptimOptimExt/jl_tj08oS" (ProcessExited(1)). │ └ @ Base loading.jl:1721 Constructing new sampler... Sampling starts... Sampling, BaytesOptim: Error During Test at /home/pkgeval/.julia/packages/Baytes/Sijx3/test/test-construction.jl:285 Got exception outside of a @test TaskFailedException nested task error: MethodError: no method matching _optimize(::Vector{Float64}, ::BaytesOptim.var"#propagate##0#propagate##1"{OptimLBFG{BaytesDiff.ℓDensityResult{Vector{Float64}, Float64}, BaytesDiff.AutomaticDiffTune{BaytesDiff.ADForward, BaytesDiff.DiffOrderOne, ForwardDiff.GradientConfig{ForwardDiff.Tag{Objective{ModelWrapper{MyBaseModel, @NamedTuple{μ::Float64, σ::Float64}, @NamedTuple{}, ParameterInfo{ReConstructor{FlattenDefault{Float64, FlattenContinuous}, FlattenConstructor{ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##64"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}, ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}}}}, ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##66"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2", ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2"}}}}, UnflattenConstructor{ModelWrappers.var"#unflatten_to_NamedTuple#construct_flatten##65"{@NamedTuple{μ::Float64, σ::Float64}, ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64, Int64}, Tuple{Int64, Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}, ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}}}}, ModelWrappers.var"#unflatten_to_NamedTupleAD#construct_flatten##67"{(:μ, :σ), ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64, Int64}, Tuple{Int64, Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3", ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3"}}}}}, ReConstructor{FlattenDefault{Float64, FlattenContinuous}, FlattenConstructor{ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##64"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}, ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}}}}, ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##66"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2", ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2"}}}}, UnflattenConstructor{ModelWrappers.var"#unflatten_to_NamedTuple#construct_flatten##65"{@NamedTuple{μ::Float64, σ::Float64}, ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64, Int64}, Tuple{Int64, Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}, ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}}}}, ModelWrappers.var"#unflatten_to_NamedTupleAD#construct_flatten##67"{(:μ, :σ), ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64, Int64}, Tuple{Int64, Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3", ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3"}}}}}, TransformConstructor{@NamedTuple{μ::DistributionConstraint{Normal{Float64}, Bijection{typeof(identity), typeof(identity)}}, σ::DistributionConstraint{Gamma{Float64}, Bijection{Base.Fix1{typeof(broadcast), typeof(log)}, Base.Fix1{typeof(broadcast), typeof(exp)}}}}}}}, Vector{Float64}, Tagged{@NamedTuple{μ::Bool}, ParameterInfo{ReConstructor{FlattenDefault{Float64, FlattenContinuous}, FlattenConstructor{ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##64"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}}}}, ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##66"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2"}}}}, UnflattenConstructor{ModelWrappers.var"#unflatten_to_NamedTuple#construct_flatten##65"{@NamedTuple{μ::Float64}, ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64}, Tuple{Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}}}}, ModelWrappers.var"#unflatten_to_NamedTupleAD#construct_flatten##67"{(:μ,), ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64}, Tuple{Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3"}}}}}, ReConstructor{FlattenDefault{Float64, FlattenContinuous}, FlattenConstructor{ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##64"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}}}}, ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##66"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2"}}}}, UnflattenConstructor{ModelWrappers.var"#unflatten_to_NamedTuple#construct_flatten##65"{@NamedTuple{μ::Float64}, ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64}, Tuple{Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}}}}, ModelWrappers.var"#unflatten_to_NamedTupleAD#construct_flatten##67"{(:μ,), ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64}, Tuple{Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3"}}}}}, TransformConstructor{@NamedTuple{μ::DistributionConstraint{Normal{Float64}, Bijection{typeof(identity), typeof(identity)}}}}}}, Float64}, Float64}, Float64, 1, Vector{ForwardDiff.Dual{ForwardDiff.Tag{Objective{ModelWrapper{MyBaseModel, @NamedTuple{μ::Float64, σ::Float64}, @NamedTuple{}, ParameterInfo{ReConstructor{FlattenDefault{Float64, FlattenContinuous}, FlattenConstructor{ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##64"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}, ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}}}}, ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##66"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2", ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2"}}}}, UnflattenConstructor{ModelWrappers.var"#unflatten_to_NamedTuple#construct_flatten##65"{@NamedTuple{μ::Float64, σ::Float64}, ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64, Int64}, Tuple{Int64, Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}, ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}}}}, ModelWrappers.var"#unflatten_to_NamedTupleAD#construct_flatten##67"{(:μ, :σ), ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64, Int64}, Tuple{Int64, Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3", ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3"}}}}}, ReConstructor{FlattenDefault{Float64, FlattenContinuous}, FlattenConstructor{ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##64"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}, ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}}}}, ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##66"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2", ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2"}}}}, UnflattenConstructor{ModelWrappers.var"#unflatten_to_NamedTuple#construct_flatten##65"{@NamedTuple{μ::Float64, σ::Float64}, ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64, Int64}, Tuple{Int64, Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}, ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}}}}, ModelWrappers.var"#unflatten_to_NamedTupleAD#construct_flatten##67"{(:μ, :σ), ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64, Int64}, Tuple{Int64, Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3", ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3"}}}}}, TransformConstructor{@NamedTuple{μ::DistributionConstraint{Normal{Float64}, Bijection{typeof(identity), typeof(identity)}}, σ::DistributionConstraint{Gamma{Float64}, Bijection{Base.Fix1{typeof(broadcast), typeof(log)}, Base.Fix1{typeof(broadcast), typeof(exp)}}}}}}}, Vector{Float64}, Tagged{@NamedTuple{μ::Bool}, ParameterInfo{ReConstructor{FlattenDefault{Float64, FlattenContinuous}, FlattenConstructor{ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##64"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}}}}, ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##66"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2"}}}}, UnflattenConstructor{ModelWrappers.var"#unflatten_to_NamedTuple#construct_flatten##65"{@NamedTuple{μ::Float64}, ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64}, Tuple{Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}}}}, ModelWrappers.var"#unflatten_to_NamedTupleAD#construct_flatten##67"{(:μ,), ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64}, Tuple{Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3"}}}}}, ReConstructor{FlattenDefault{Float64, FlattenContinuous}, FlattenConstructor{ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##64"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}}}}, ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##66"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2"}}}}, UnflattenConstructor{ModelWrappers.var"#unflatten_to_NamedTuple#construct_flatten##65"{@NamedTuple{μ::Float64}, ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64}, Tuple{Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}}}}, ModelWrappers.var"#unflatten_to_NamedTupleAD#construct_flatten##67"{(:μ,), ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64}, Tuple{Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3"}}}}}, TransformConstructor{@NamedTuple{μ::DistributionConstraint{Normal{Float64}, Bijection{typeof(identity), typeof(identity)}}}}}}, Float64}, Float64}, Float64, 1}}}}}, Objective{ModelWrapper{MyBaseModel, @NamedTuple{μ::Float64, σ::Float64}, @NamedTuple{}, ParameterInfo{ReConstructor{FlattenDefault{Float64, FlattenContinuous}, FlattenConstructor{ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##64"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}, ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}}}}, ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##66"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2", ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2"}}}}, UnflattenConstructor{ModelWrappers.var"#unflatten_to_NamedTuple#construct_flatten##65"{@NamedTuple{μ::Float64, σ::Float64}, ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64, Int64}, Tuple{Int64, Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}, ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}}}}, ModelWrappers.var"#unflatten_to_NamedTupleAD#construct_flatten##67"{(:μ, :σ), ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64, Int64}, Tuple{Int64, Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3", ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3"}}}}}, ReConstructor{FlattenDefault{Float64, FlattenContinuous}, FlattenConstructor{ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##64"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}, ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}}}}, ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##66"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2", ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2"}}}}, UnflattenConstructor{ModelWrappers.var"#unflatten_to_NamedTuple#construct_flatten##65"{@NamedTuple{μ::Float64, σ::Float64}, ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64, Int64}, Tuple{Int64, Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}, ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}}}}, ModelWrappers.var"#unflatten_to_NamedTupleAD#construct_flatten##67"{(:μ, :σ), ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64, Int64}, Tuple{Int64, Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3", ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3"}}}}}, TransformConstructor{@NamedTuple{μ::DistributionConstraint{Normal{Float64}, Bijection{typeof(identity), typeof(identity)}}, σ::DistributionConstraint{Gamma{Float64}, Bijection{Base.Fix1{typeof(broadcast), typeof(log)}, Base.Fix1{typeof(broadcast), typeof(exp)}}}}}}}, Vector{Float64}, Tagged{@NamedTuple{μ::Bool}, ParameterInfo{ReConstructor{FlattenDefault{Float64, FlattenContinuous}, FlattenConstructor{ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##64"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}}}}, ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##66"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2"}}}}, UnflattenConstructor{ModelWrappers.var"#unflatten_to_NamedTuple#construct_flatten##65"{@NamedTuple{μ::Float64}, ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64}, Tuple{Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}}}}, ModelWrappers.var"#unflatten_to_NamedTupleAD#construct_flatten##67"{(:μ,), ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64}, Tuple{Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3"}}}}}, ReConstructor{FlattenDefault{Float64, FlattenContinuous}, FlattenConstructor{ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##64"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}}}}, ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##66"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2"}}}}, UnflattenConstructor{ModelWrappers.var"#unflatten_to_NamedTuple#construct_flatten##65"{@NamedTuple{μ::Float64}, ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64}, Tuple{Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}}}}, ModelWrappers.var"#unflatten_to_NamedTupleAD#construct_flatten##67"{(:μ,), ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64}, Tuple{Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3"}}}}}, TransformConstructor{@NamedTuple{μ::DistributionConstraint{Normal{Float64}, Bijection{typeof(identity), typeof(identity)}}}}}}, Float64}, Float64}, ::Int64) The function `_optimize` exists, but no method is defined for this combination of argument types. Stacktrace: [1] propagate(_rng::Random.Xoshiro, kernel::OptimLBFG{BaytesDiff.ℓDensityResult{Vector{Float64}, Float64}, BaytesDiff.AutomaticDiffTune{BaytesDiff.ADForward, BaytesDiff.DiffOrderOne, ForwardDiff.GradientConfig{ForwardDiff.Tag{Objective{ModelWrapper{MyBaseModel, @NamedTuple{μ::Float64, σ::Float64}, @NamedTuple{}, ParameterInfo{ReConstructor{FlattenDefault{Float64, FlattenContinuous}, FlattenConstructor{ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##64"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}, ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}}}}, ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##66"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2", ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2"}}}}, UnflattenConstructor{ModelWrappers.var"#unflatten_to_NamedTuple#construct_flatten##65"{@NamedTuple{μ::Float64, σ::Float64}, ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64, Int64}, Tuple{Int64, Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}, ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}}}}, ModelWrappers.var"#unflatten_to_NamedTupleAD#construct_flatten##67"{(:μ, :σ), ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64, Int64}, Tuple{Int64, Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3", ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3"}}}}}, ReConstructor{FlattenDefault{Float64, FlattenContinuous}, FlattenConstructor{ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##64"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}, ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}}}}, ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##66"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2", ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2"}}}}, UnflattenConstructor{ModelWrappers.var"#unflatten_to_NamedTuple#construct_flatten##65"{@NamedTuple{μ::Float64, σ::Float64}, ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64, Int64}, Tuple{Int64, Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}, ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}}}}, ModelWrappers.var"#unflatten_to_NamedTupleAD#construct_flatten##67"{(:μ, :σ), ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64, Int64}, Tuple{Int64, Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3", ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3"}}}}}, TransformConstructor{@NamedTuple{μ::DistributionConstraint{Normal{Float64}, Bijection{typeof(identity), typeof(identity)}}, σ::DistributionConstraint{Gamma{Float64}, Bijection{Base.Fix1{typeof(broadcast), typeof(log)}, Base.Fix1{typeof(broadcast), typeof(exp)}}}}}}}, Vector{Float64}, Tagged{@NamedTuple{μ::Bool}, ParameterInfo{ReConstructor{FlattenDefault{Float64, FlattenContinuous}, FlattenConstructor{ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##64"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}}}}, ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##66"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2"}}}}, UnflattenConstructor{ModelWrappers.var"#unflatten_to_NamedTuple#construct_flatten##65"{@NamedTuple{μ::Float64}, ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64}, Tuple{Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}}}}, ModelWrappers.var"#unflatten_to_NamedTupleAD#construct_flatten##67"{(:μ,), ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64}, Tuple{Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3"}}}}}, ReConstructor{FlattenDefault{Float64, FlattenContinuous}, FlattenConstructor{ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##64"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}}}}, ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##66"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2"}}}}, UnflattenConstructor{ModelWrappers.var"#unflatten_to_NamedTuple#construct_flatten##65"{@NamedTuple{μ::Float64}, ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64}, Tuple{Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}}}}, ModelWrappers.var"#unflatten_to_NamedTupleAD#construct_flatten##67"{(:μ,), ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64}, Tuple{Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3"}}}}}, TransformConstructor{@NamedTuple{μ::DistributionConstraint{Normal{Float64}, Bijection{typeof(identity), typeof(identity)}}}}}}, Float64}, Float64}, Float64, 1, Vector{ForwardDiff.Dual{ForwardDiff.Tag{Objective{ModelWrapper{MyBaseModel, @NamedTuple{μ::Float64, σ::Float64}, @NamedTuple{}, ParameterInfo{ReConstructor{FlattenDefault{Float64, FlattenContinuous}, FlattenConstructor{ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##64"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}, ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}}}}, ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##66"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2", ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2"}}}}, UnflattenConstructor{ModelWrappers.var"#unflatten_to_NamedTuple#construct_flatten##65"{@NamedTuple{μ::Float64, σ::Float64}, ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64, Int64}, Tuple{Int64, Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}, ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}}}}, ModelWrappers.var"#unflatten_to_NamedTupleAD#construct_flatten##67"{(:μ, :σ), ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64, Int64}, Tuple{Int64, Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3", ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3"}}}}}, ReConstructor{FlattenDefault{Float64, FlattenContinuous}, FlattenConstructor{ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##64"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}, ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}}}}, ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##66"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2", ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2"}}}}, UnflattenConstructor{ModelWrappers.var"#unflatten_to_NamedTuple#construct_flatten##65"{@NamedTuple{μ::Float64, σ::Float64}, ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64, Int64}, Tuple{Int64, Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}, ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}}}}, ModelWrappers.var"#unflatten_to_NamedTupleAD#construct_flatten##67"{(:μ, :σ), ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64, Int64}, Tuple{Int64, Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3", ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3"}}}}}, TransformConstructor{@NamedTuple{μ::DistributionConstraint{Normal{Float64}, Bijection{typeof(identity), typeof(identity)}}, σ::DistributionConstraint{Gamma{Float64}, Bijection{Base.Fix1{typeof(broadcast), typeof(log)}, Base.Fix1{typeof(broadcast), typeof(exp)}}}}}}}, Vector{Float64}, Tagged{@NamedTuple{μ::Bool}, ParameterInfo{ReConstructor{FlattenDefault{Float64, FlattenContinuous}, FlattenConstructor{ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##64"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}}}}, ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##66"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2"}}}}, UnflattenConstructor{ModelWrappers.var"#unflatten_to_NamedTuple#construct_flatten##65"{@NamedTuple{μ::Float64}, ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64}, Tuple{Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}}}}, ModelWrappers.var"#unflatten_to_NamedTupleAD#construct_flatten##67"{(:μ,), ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64}, Tuple{Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3"}}}}}, ReConstructor{FlattenDefault{Float64, FlattenContinuous}, FlattenConstructor{ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##64"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}}}}, ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##66"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2"}}}}, UnflattenConstructor{ModelWrappers.var"#unflatten_to_NamedTuple#construct_flatten##65"{@NamedTuple{μ::Float64}, ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64}, Tuple{Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}}}}, ModelWrappers.var"#unflatten_to_NamedTupleAD#construct_flatten##67"{(:μ,), ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64}, Tuple{Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3"}}}}}, TransformConstructor{@NamedTuple{μ::DistributionConstraint{Normal{Float64}, Bijection{typeof(identity), typeof(identity)}}}}}}, Float64}, Float64}, Float64, 1}}}}}, tune::OptimTune{Tagged{@NamedTuple{μ::Bool}, ParameterInfo{ReConstructor{FlattenDefault{Float64, FlattenContinuous}, FlattenConstructor{ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##64"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}}}}, ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##66"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2"}}}}, UnflattenConstructor{ModelWrappers.var"#unflatten_to_NamedTuple#construct_flatten##65"{@NamedTuple{μ::Float64}, ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64}, Tuple{Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}}}}, ModelWrappers.var"#unflatten_to_NamedTupleAD#construct_flatten##67"{(:μ,), ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64}, Tuple{Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3"}}}}}, ReConstructor{FlattenDefault{Float64, FlattenContinuous}, FlattenConstructor{ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##64"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}}}}, ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##66"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2"}}}}, UnflattenConstructor{ModelWrappers.var"#unflatten_to_NamedTuple#construct_flatten##65"{@NamedTuple{μ::Float64}, ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64}, Tuple{Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}}}}, ModelWrappers.var"#unflatten_to_NamedTupleAD#construct_flatten##67"{(:μ,), ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64}, Tuple{Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3"}}}}}, TransformConstructor{@NamedTuple{μ::DistributionConstraint{Normal{Float64}, Bijection{typeof(identity), typeof(identity)}}}}}}, LBFGTune{Float64}, UpdateFalse}, objective::Objective{ModelWrapper{MyBaseModel, @NamedTuple{μ::Float64, σ::Float64}, @NamedTuple{}, ParameterInfo{ReConstructor{FlattenDefault{Float64, FlattenContinuous}, FlattenConstructor{ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##64"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}, ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}}}}, ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##66"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2", ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2"}}}}, UnflattenConstructor{ModelWrappers.var"#unflatten_to_NamedTuple#construct_flatten##65"{@NamedTuple{μ::Float64, σ::Float64}, ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64, Int64}, Tuple{Int64, Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}, ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}}}}, ModelWrappers.var"#unflatten_to_NamedTupleAD#construct_flatten##67"{(:μ, :σ), ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64, Int64}, Tuple{Int64, Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3", ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3"}}}}}, ReConstructor{FlattenDefault{Float64, FlattenContinuous}, FlattenConstructor{ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##64"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}, ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}}}}, ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##66"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2", ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2"}}}}, UnflattenConstructor{ModelWrappers.var"#unflatten_to_NamedTuple#construct_flatten##65"{@NamedTuple{μ::Float64, σ::Float64}, ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64, Int64}, Tuple{Int64, Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}, ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}}}}, ModelWrappers.var"#unflatten_to_NamedTupleAD#construct_flatten##67"{(:μ, :σ), ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64, Int64}, Tuple{Int64, Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3", ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3"}}}}}, TransformConstructor{@NamedTuple{μ::DistributionConstraint{Normal{Float64}, Bijection{typeof(identity), typeof(identity)}}, σ::DistributionConstraint{Gamma{Float64}, Bijection{Base.Fix1{typeof(broadcast), typeof(log)}, Base.Fix1{typeof(broadcast), typeof(exp)}}}}}}}, Vector{Float64}, Tagged{@NamedTuple{μ::Bool}, ParameterInfo{ReConstructor{FlattenDefault{Float64, FlattenContinuous}, FlattenConstructor{ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##64"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}}}}, ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##66"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2"}}}}, UnflattenConstructor{ModelWrappers.var"#unflatten_to_NamedTuple#construct_flatten##65"{@NamedTuple{μ::Float64}, ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64}, Tuple{Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}}}}, ModelWrappers.var"#unflatten_to_NamedTupleAD#construct_flatten##67"{(:μ,), ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64}, Tuple{Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3"}}}}}, ReConstructor{FlattenDefault{Float64, FlattenContinuous}, FlattenConstructor{ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##64"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}}}}, ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##66"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2"}}}}, UnflattenConstructor{ModelWrappers.var"#unflatten_to_NamedTuple#construct_flatten##65"{@NamedTuple{μ::Float64}, ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64}, Tuple{Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}}}}, ModelWrappers.var"#unflatten_to_NamedTupleAD#construct_flatten##67"{(:μ,), ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64}, Tuple{Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3"}}}}}, TransformConstructor{@NamedTuple{μ::DistributionConstraint{Normal{Float64}, Bijection{typeof(identity), typeof(identity)}}}}}}, Float64}) @ BaytesOptim ~/.julia/packages/BaytesOptim/VHjJJ/src/Kernels/LBFG/kernel.jl:76 [2] propose(_rng::Random.Xoshiro, optim::Optimizer{OptimLBFG{BaytesDiff.ℓDensityResult{Vector{Float64}, Float64}, BaytesDiff.AutomaticDiffTune{BaytesDiff.ADForward, BaytesDiff.DiffOrderOne, ForwardDiff.GradientConfig{ForwardDiff.Tag{Objective{ModelWrapper{MyBaseModel, @NamedTuple{μ::Float64, σ::Float64}, @NamedTuple{}, ParameterInfo{ReConstructor{FlattenDefault{Float64, FlattenContinuous}, FlattenConstructor{ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##64"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}, ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}}}}, 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Trace{TraceSummary{IterationTempering{UpdateFalse, Float64}, Vector{DataTune{Batch, Nothing, Nothing}}, SampleDefault{Batch, IterationTempering{UpdateFalse, Float64}, ProgressReport{SilentLog, @NamedTuple{dt::Float64, desc::String, color::Symbol, showspeed::Bool}}}, SampleInfo{Baytes.PrintedParameter{Tuple{Symbol}, Tuple{Symbol}}, UpdateFalse, UpdateFalse}}, @NamedTuple{μ::Float64, σ::Float64}, Tuple{Vector{OptimDiagnostics{Float64, DiagnosticsLBFG, Nothing, Nothing}}}}, Vector{Tuple{Optimizer{OptimLBFG{BaytesDiff.ℓDensityResult{Vector{Float64}, Float64}, BaytesDiff.AutomaticDiffTune{BaytesDiff.ADForward, BaytesDiff.DiffOrderOne, ForwardDiff.GradientConfig{ForwardDiff.Tag{Objective{ModelWrapper{MyBaseModel, @NamedTuple{μ::Float64, σ::Float64}, @NamedTuple{}, ParameterInfo{ReConstructor{FlattenDefault{Float64, FlattenContinuous}, 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ModelWrappers.var"#unflatten_to_NamedTupleAD#construct_flatten##67"{(:μ, :σ), ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64, Int64}, Tuple{Int64, Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3", ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3"}}}}}, ReConstructor{FlattenDefault{Float64, FlattenContinuous}, FlattenConstructor{ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##64"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}, ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}}}}, ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##66"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2", ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2"}}}}, 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Tagged{@NamedTuple{μ::Bool}, ParameterInfo{ReConstructor{FlattenDefault{Float64, FlattenContinuous}, FlattenConstructor{ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##64"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}}}}, ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##66"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2"}}}}, UnflattenConstructor{ModelWrappers.var"#unflatten_to_NamedTuple#construct_flatten##65"{@NamedTuple{μ::Float64}, ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64}, Tuple{Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}}}}, ModelWrappers.var"#unflatten_to_NamedTupleAD#construct_flatten##67"{(:μ,), ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64}, Tuple{Int64}, 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ModelWrappers.var"#unflatten_to_NamedTupleAD#construct_flatten##67"{(:μ, :σ), ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64, Int64}, Tuple{Int64, Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3", ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3"}}}}}, TransformConstructor{@NamedTuple{μ::DistributionConstraint{Normal{Float64}, Bijection{typeof(identity), typeof(identity)}}, σ::DistributionConstraint{Gamma{Float64}, Bijection{Base.Fix1{typeof(broadcast), typeof(log)}, Base.Fix1{typeof(broadcast), typeof(exp)}}}}}}}, Vector{Float64}, Tagged{@NamedTuple{μ::Bool}, ParameterInfo{ReConstructor{FlattenDefault{Float64, FlattenContinuous}, FlattenConstructor{ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##64"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}}}}, ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##66"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2"}}}}, UnflattenConstructor{ModelWrappers.var"#unflatten_to_NamedTuple#construct_flatten##65"{@NamedTuple{μ::Float64}, ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64}, Tuple{Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}}}}, ModelWrappers.var"#unflatten_to_NamedTupleAD#construct_flatten##67"{(:μ,), ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64}, Tuple{Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3"}}}}}, ReConstructor{FlattenDefault{Float64, FlattenContinuous}, 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TransformConstructor{@NamedTuple{μ::DistributionConstraint{Normal{Float64}, Bijection{typeof(identity), typeof(identity)}}}}}}, Float64}, Float64}, Float64, 1}}}}}, OptimTune{Tagged{@NamedTuple{μ::Bool}, ParameterInfo{ReConstructor{FlattenDefault{Float64, FlattenContinuous}, FlattenConstructor{ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##64"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}}}}, ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##66"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2"}}}}, UnflattenConstructor{ModelWrappers.var"#unflatten_to_NamedTuple#construct_flatten##65"{@NamedTuple{μ::Float64}, ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64}, Tuple{Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}}}}, ModelWrappers.var"#unflatten_to_NamedTupleAD#construct_flatten##67"{(:μ,), ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64}, Tuple{Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3"}}}}}, ReConstructor{FlattenDefault{Float64, FlattenContinuous}, FlattenConstructor{ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##64"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}}}}, ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##66"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2"}}}}, UnflattenConstructor{ModelWrappers.var"#unflatten_to_NamedTuple#construct_flatten##65"{@NamedTuple{μ::Float64}, ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64}, Tuple{Int64}, 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ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##66"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2", ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2"}}}}, UnflattenConstructor{ModelWrappers.var"#unflatten_to_NamedTuple#construct_flatten##65"{@NamedTuple{μ::Float64, σ::Float64}, ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64, Int64}, Tuple{Int64, Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}, ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}}}}, ModelWrappers.var"#unflatten_to_NamedTupleAD#construct_flatten##67"{(:μ, :σ), ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64, Int64}, Tuple{Int64, Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3", ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3"}}}}}, ReConstructor{FlattenDefault{Float64, FlattenContinuous}, FlattenConstructor{ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##64"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}, ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}}}}, ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##66"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2", ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2"}}}}, UnflattenConstructor{ModelWrappers.var"#unflatten_to_NamedTuple#construct_flatten##65"{@NamedTuple{μ::Float64, σ::Float64}, ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64, Int64}, Tuple{Int64, Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}, ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}}}}, ModelWrappers.var"#unflatten_to_NamedTupleAD#construct_flatten##67"{(:μ, :σ), ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64, Int64}, Tuple{Int64, Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3", ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3"}}}}}, TransformConstructor{@NamedTuple{μ::DistributionConstraint{Normal{Float64}, Bijection{typeof(identity), typeof(identity)}}, σ::DistributionConstraint{Gamma{Float64}, Bijection{Base.Fix1{typeof(broadcast), typeof(log)}, Base.Fix1{typeof(broadcast), typeof(exp)}}}}}}}}, Vector{Float64}, SilentLog, UpdateFalse, Int64, Int64, ProgressMeter.Progress, Vector{DataTune{Batch, Nothing, Nothing}}, IterationTempering{UpdateFalse, Float64}, Base.OneTo{Int64}}}, static::Bool) @ Base.Threads ./threadingconstructs.jl:196 [2] macro expansion @ ./threadingconstructs.jl:213 [inlined] [3] propose!(_rng::Random.Xoshiro, trace::Trace{TraceSummary{IterationTempering{UpdateFalse, Float64}, Vector{DataTune{Batch, Nothing, Nothing}}, SampleDefault{Batch, IterationTempering{UpdateFalse, Float64}, ProgressReport{SilentLog, @NamedTuple{dt::Float64, desc::String, color::Symbol, showspeed::Bool}}}, SampleInfo{Baytes.PrintedParameter{Tuple{Symbol}, Tuple{Symbol}}, UpdateFalse, UpdateFalse}}, @NamedTuple{μ::Float64, σ::Float64}, Tuple{Vector{OptimDiagnostics{Float64, DiagnosticsLBFG, Nothing, Nothing}}}}, algorithmᵛ::Vector{Tuple{Optimizer{OptimLBFG{BaytesDiff.ℓDensityResult{Vector{Float64}, Float64}, BaytesDiff.AutomaticDiffTune{BaytesDiff.ADForward, BaytesDiff.DiffOrderOne, ForwardDiff.GradientConfig{ForwardDiff.Tag{Objective{ModelWrapper{MyBaseModel, @NamedTuple{μ::Float64, σ::Float64}, @NamedTuple{}, ParameterInfo{ReConstructor{FlattenDefault{Float64, FlattenContinuous}, FlattenConstructor{ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##64"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}, ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}}}}, ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##66"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2", ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2"}}}}, UnflattenConstructor{ModelWrappers.var"#unflatten_to_NamedTuple#construct_flatten##65"{@NamedTuple{μ::Float64, σ::Float64}, ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64, Int64}, Tuple{Int64, Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}, ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}}}}, ModelWrappers.var"#unflatten_to_NamedTupleAD#construct_flatten##67"{(:μ, :σ), ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64, Int64}, Tuple{Int64, Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3", ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3"}}}}}, ReConstructor{FlattenDefault{Float64, FlattenContinuous}, FlattenConstructor{ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##64"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}, ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}}}}, ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##66"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2", ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2"}}}}, UnflattenConstructor{ModelWrappers.var"#unflatten_to_NamedTuple#construct_flatten##65"{@NamedTuple{μ::Float64, σ::Float64}, ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64, Int64}, Tuple{Int64, Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}, ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}}}}, ModelWrappers.var"#unflatten_to_NamedTupleAD#construct_flatten##67"{(:μ, :σ), ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64, Int64}, Tuple{Int64, Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3", ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3"}}}}}, TransformConstructor{@NamedTuple{μ::DistributionConstraint{Normal{Float64}, Bijection{typeof(identity), typeof(identity)}}, σ::DistributionConstraint{Gamma{Float64}, Bijection{Base.Fix1{typeof(broadcast), typeof(log)}, Base.Fix1{typeof(broadcast), typeof(exp)}}}}}}}, Vector{Float64}, Tagged{@NamedTuple{μ::Bool}, ParameterInfo{ReConstructor{FlattenDefault{Float64, FlattenContinuous}, FlattenConstructor{ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##64"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}}}}, ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##66"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2"}}}}, UnflattenConstructor{ModelWrappers.var"#unflatten_to_NamedTuple#construct_flatten##65"{@NamedTuple{μ::Float64}, ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64}, Tuple{Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}}}}, ModelWrappers.var"#unflatten_to_NamedTupleAD#construct_flatten##67"{(:μ,), ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64}, Tuple{Int64}, 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FlattenConstructor{ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##64"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}, ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}}}}, ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##66"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2", ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2"}}}}, UnflattenConstructor{ModelWrappers.var"#unflatten_to_NamedTuple#construct_flatten##65"{@NamedTuple{μ::Float64, σ::Float64}, ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64, Int64}, Tuple{Int64, Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}, ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}}}}, ModelWrappers.var"#unflatten_to_NamedTupleAD#construct_flatten##67"{(:μ, :σ), ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64, Int64}, Tuple{Int64, Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3", ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3"}}}}}, TransformConstructor{@NamedTuple{μ::DistributionConstraint{Normal{Float64}, Bijection{typeof(identity), typeof(identity)}}, σ::DistributionConstraint{Gamma{Float64}, Bijection{Base.Fix1{typeof(broadcast), typeof(log)}, Base.Fix1{typeof(broadcast), typeof(exp)}}}}}}}, Vector{Float64}, Tagged{@NamedTuple{μ::Bool}, ParameterInfo{ReConstructor{FlattenDefault{Float64, FlattenContinuous}, FlattenConstructor{ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##64"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}}}}, ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##66"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2"}}}}, UnflattenConstructor{ModelWrappers.var"#unflatten_to_NamedTuple#construct_flatten##65"{@NamedTuple{μ::Float64}, ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64}, Tuple{Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}}}}, ModelWrappers.var"#unflatten_to_NamedTupleAD#construct_flatten##67"{(:μ,), ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64}, Tuple{Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3"}}}}}, ReConstructor{FlattenDefault{Float64, FlattenContinuous}, FlattenConstructor{ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##64"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}}}}, ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##66"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2"}}}}, UnflattenConstructor{ModelWrappers.var"#unflatten_to_NamedTuple#construct_flatten##65"{@NamedTuple{μ::Float64}, ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64}, Tuple{Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}}}}, ModelWrappers.var"#unflatten_to_NamedTupleAD#construct_flatten##67"{(:μ,), ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64}, Tuple{Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3"}}}}}, TransformConstructor{@NamedTuple{μ::DistributionConstraint{Normal{Float64}, Bijection{typeof(identity), typeof(identity)}}}}}}, Float64}, Float64}, Float64, 1}}}}}, OptimTune{Tagged{@NamedTuple{μ::Bool}, ParameterInfo{ReConstructor{FlattenDefault{Float64, FlattenContinuous}, FlattenConstructor{ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##64"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}}}}, ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##66"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2"}}}}, UnflattenConstructor{ModelWrappers.var"#unflatten_to_NamedTuple#construct_flatten##65"{@NamedTuple{μ::Float64}, ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64}, Tuple{Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}}}}, ModelWrappers.var"#unflatten_to_NamedTupleAD#construct_flatten##67"{(:μ,), ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64}, Tuple{Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3"}}}}}, ReConstructor{FlattenDefault{Float64, FlattenContinuous}, FlattenConstructor{ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##64"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}}}}, ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##66"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2"}}}}, UnflattenConstructor{ModelWrappers.var"#unflatten_to_NamedTuple#construct_flatten##65"{@NamedTuple{μ::Float64}, ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64}, Tuple{Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}}}}, ModelWrappers.var"#unflatten_to_NamedTupleAD#construct_flatten##67"{(:μ,), ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64}, Tuple{Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3"}}}}}, TransformConstructor{@NamedTuple{μ::DistributionConstraint{Normal{Float64}, Bijection{typeof(identity), typeof(identity)}}}}}}, LBFGTune{Float64}, UpdateFalse}}}}, modelᵛ::Vector{ModelWrapper{MyBaseModel, @NamedTuple{μ::Float64, σ::Float64}, @NamedTuple{}, ParameterInfo{ReConstructor{FlattenDefault{Float64, FlattenContinuous}, FlattenConstructor{ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##64"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}, ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}}}}, ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##66"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2", ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2"}}}}, UnflattenConstructor{ModelWrappers.var"#unflatten_to_NamedTuple#construct_flatten##65"{@NamedTuple{μ::Float64, σ::Float64}, ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64, Int64}, Tuple{Int64, Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}, ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}}}}, ModelWrappers.var"#unflatten_to_NamedTupleAD#construct_flatten##67"{(:μ, :σ), ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64, Int64}, Tuple{Int64, Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3", ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3"}}}}}, ReConstructor{FlattenDefault{Float64, FlattenContinuous}, FlattenConstructor{ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##64"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}, ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}}}}, ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##66"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2", ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2"}}}}, UnflattenConstructor{ModelWrappers.var"#unflatten_to_NamedTuple#construct_flatten##65"{@NamedTuple{μ::Float64, σ::Float64}, ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64, Int64}, Tuple{Int64, Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}, ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}}}}, ModelWrappers.var"#unflatten_to_NamedTupleAD#construct_flatten##67"{(:μ, :σ), ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64, Int64}, Tuple{Int64, Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3", ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3"}}}}}, TransformConstructor{@NamedTuple{μ::DistributionConstraint{Normal{Float64}, Bijection{typeof(identity), typeof(identity)}}, σ::DistributionConstraint{Gamma{Float64}, Bijection{Base.Fix1{typeof(broadcast), typeof(log)}, Base.Fix1{typeof(broadcast), typeof(exp)}}}}}}}}, data::Vector{Float64}) @ Baytes ~/.julia/packages/Baytes/Sijx3/src/sampling/trace.jl:110 [4] sample(_rng::Random.Xoshiro, model::ModelWrapper{MyBaseModel, @NamedTuple{μ::Float64, σ::Float64}, @NamedTuple{}, ParameterInfo{ReConstructor{FlattenDefault{Float64, FlattenContinuous}, FlattenConstructor{ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##64"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}, ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}}}}, ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##66"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2", ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2"}}}}, UnflattenConstructor{ModelWrappers.var"#unflatten_to_NamedTuple#construct_flatten##65"{@NamedTuple{μ::Float64, σ::Float64}, ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64, Int64}, Tuple{Int64, Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}, ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}}}}, ModelWrappers.var"#unflatten_to_NamedTupleAD#construct_flatten##67"{(:μ, :σ), ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64, Int64}, Tuple{Int64, Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3", ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3"}}}}}, ReConstructor{FlattenDefault{Float64, FlattenContinuous}, FlattenConstructor{ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##64"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}, ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}}}}, ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##66"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2", ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2"}}}}, UnflattenConstructor{ModelWrappers.var"#unflatten_to_NamedTuple#construct_flatten##65"{@NamedTuple{μ::Float64, σ::Float64}, ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64, Int64}, Tuple{Int64, Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}, ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}}}}, ModelWrappers.var"#unflatten_to_NamedTupleAD#construct_flatten##67"{(:μ, :σ), ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64, Int64}, Tuple{Int64, Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3", ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3"}}}}}, TransformConstructor{@NamedTuple{μ::DistributionConstraint{Normal{Float64}, Bijection{typeof(identity), typeof(identity)}}, σ::DistributionConstraint{Gamma{Float64}, Bijection{Base.Fix1{typeof(broadcast), typeof(log)}, Base.Fix1{typeof(broadcast), typeof(exp)}}}}}}}, data::Vector{Float64}, args::OptimConstructor{UnionAll, Tuple{Symbol}, OptimDefault{@NamedTuple{iterations::Int64}, Symbol, NoInitialization, UpdateFalse}}; default::SampleDefault{Batch, IterationTempering{UpdateFalse, Float64}, ProgressReport{SilentLog, @NamedTuple{dt::Float64, desc::String, color::Symbol, showspeed::Bool}}}) @ Baytes ~/.julia/packages/Baytes/Sijx3/src/sampling/sample.jl:63 [5] kwcall(::@NamedTuple{default::SampleDefault{Batch, IterationTempering{UpdateFalse, Float64}, ProgressReport{SilentLog, @NamedTuple{dt::Float64, desc::String, color::Symbol, showspeed::Bool}}}}, ::typeof(sample), _rng::Random.Xoshiro, model::ModelWrapper{MyBaseModel, @NamedTuple{μ::Float64, σ::Float64}, @NamedTuple{}, ParameterInfo{ReConstructor{FlattenDefault{Float64, FlattenContinuous}, FlattenConstructor{ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##64"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}, ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}}}}, ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##66"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2", ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2"}}}}, UnflattenConstructor{ModelWrappers.var"#unflatten_to_NamedTuple#construct_flatten##65"{@NamedTuple{μ::Float64, σ::Float64}, ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64, Int64}, Tuple{Int64, Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}, ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}}}}, ModelWrappers.var"#unflatten_to_NamedTupleAD#construct_flatten##67"{(:μ, :σ), ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64, Int64}, Tuple{Int64, Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3", ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3"}}}}}, ReConstructor{FlattenDefault{Float64, FlattenContinuous}, FlattenConstructor{ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##64"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}, ModelWrappers.var"#flatten_to_Real#construct_flatten##0"{Float64}}}}, ModelWrappers.var"#flatten_to_NamedTuple#construct_flatten##66"{ModelWrappers.var"#construct_flatten_Tuple#construct_flatten##54"{Tuple{ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2", ModelWrappers.var"#flatten_to_Real_AD#construct_flatten##2"}}}}, UnflattenConstructor{ModelWrappers.var"#unflatten_to_NamedTuple#construct_flatten##65"{@NamedTuple{μ::Float64, σ::Float64}, ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64, Int64}, Tuple{Int64, Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}, ModelWrappers.var"#unflatten_to_Real#construct_flatten##1"{Float64}}}}, ModelWrappers.var"#unflatten_to_NamedTupleAD#construct_flatten##67"{(:μ, :σ), ModelWrappers.var"#construct_unflatten_Tuple#construct_flatten##57"{Tuple{Int64, Int64}, Tuple{Int64, Int64}, Tuple{ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3", ModelWrappers.var"#unflatten_to_Real_AD#construct_flatten##3"}}}}}, TransformConstructor{@NamedTuple{μ::DistributionConstraint{Normal{Float64}, Bijection{typeof(identity), typeof(identity)}}, σ::DistributionConstraint{Gamma{Float64}, Bijection{Base.Fix1{typeof(broadcast), typeof(log)}, Base.Fix1{typeof(broadcast), typeof(exp)}}}}}}}, data::Vector{Float64}, args::OptimConstructor{UnionAll, Tuple{Symbol}, OptimDefault{@NamedTuple{iterations::Int64}, Symbol, NoInitialization, UpdateFalse}}) @ Baytes ~/.julia/packages/Baytes/Sijx3/src/sampling/sample.jl:35 [6] top-level scope @ ~/.julia/packages/Baytes/Sijx3/test/test-construction.jl:286 [7] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:1961 [inlined] [8] macro expansion @ ~/.julia/packages/Baytes/Sijx3/test/test-construction.jl:329 [inlined] [9] include(mapexpr::Function, mod::Module, _path::String) @ Base ./Base.jl:310 [10] top-level scope @ ~/.julia/packages/Baytes/Sijx3/test/runtests.jl:26 [11] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:1961 [inlined] [12] macro expansion @ ~/.julia/packages/Baytes/Sijx3/test/runtests.jl:26 [inlined] [13] include(mapexpr::Function, mod::Module, _path::String) @ Base ./Base.jl:310 [14] top-level scope @ none:6 [15] eval(m::Module, e::Any) @ Core ./boot.jl:489 [16] exec_options(opts::Base.JLOptions) @ Base ./client.jl:310 [17] _start() @ Base ./client.jl:577 Max iterations in Expanding/Rolling datatune set to 900. Iterations in SampleDefault are 10000. Sampling iterations set to 900 Max iterations in Expanding/Rolling datatune set to 900. Iterations in SampleDefault are 10. Sampling iterations set to 10 Constructing new sampler... Sampling starts... Constructing new sampler... Sampling starts... Constructing new sampler... Sampling starts... Sampling starts... Constructing new sampler... Sampling starts... Constructing new sampler... Sampling starts... Constructing new sampler... Sampling starts... Sampling starts... Constructing new sampler... Sampling starts... Constructing new sampler... Sampling starts... Constructing new sampler... Sampling starts... Sampling starts... Constructing new sampler... Sampling starts... Constructing new sampler... Sampling starts... Constructing new sampler... Sampling starts... Sampling starts... Constructing new sampler... Sampling starts... Constructing new sampler... Sampling starts... Constructing new sampler... Sampling starts... Sampling starts... Constructing new sampler... Sampling starts... Constructing new sampler... Sampling starts... Constructing new sampler... Sampling starts... Sampling starts... Constructing new sampler... Sampling starts... Constructing new sampler... Sampling starts... Constructing new sampler... Sampling starts... Sampling starts... Constructing new sampler... Sampling starts... Constructing new sampler... Sampling starts... Constructing new sampler... Sampling starts... Sampling starts... Test Summary: | Pass Error Total Time All tests | 166 1 167 10m54.9s Sampling, type conversion | 72 72 4m20.9s Sampling, Chain Management | 16 16 44.1s Sampling, printing and ConsoleLog | 24 24 1m28.2s Sampling, Sequential Estimation | 32 32 2m31.8s Sampling, BaytesOptim | 1 1 8.6s Utility, maxiterations | 2 2 0.0s Utility, check if chain stuck | 4 4 0.4s Sampling, type conversion | 16 16 52.4s RNG of the outermost testset: Random.Xoshiro(0x79cd38ed674d9fae, 0xb86395e0d9f3d2a3, 0x2f03d2c55be9899d, 0x66b4c0ada51b2d13, 0x5cfc5d2a4477032d) ERROR: LoadError: Some tests did not pass: 166 passed, 0 failed, 1 errored, 0 broken. in expression starting at /home/pkgeval/.julia/packages/Baytes/Sijx3/test/runtests.jl:25 Testing failed after 891.82s ERROR: LoadError: Package Baytes errored during testing Stacktrace: [1] pkgerror(msg::String) @ Pkg.Types /opt/julia/share/julia/stdlib/v1.14/Pkg/src/Types.jl:68 [2] test(ctx::Pkg.Types.Context, pkgs::Vector{PackageSpec}; coverage::Bool, julia_args::Cmd, test_args::Cmd, test_fn::Nothing, force_latest_compatible_version::Bool, allow_earlier_backwards_compatible_versions::Bool, allow_reresolve::Bool) @ Pkg.Operations /opt/julia/share/julia/stdlib/v1.14/Pkg/src/Operations.jl:3053 [3] test @ /opt/julia/share/julia/stdlib/v1.14/Pkg/src/Operations.jl:2902 [inlined] [4] test(ctx::Pkg.Types.Context, pkgs::Vector{PackageSpec}; coverage::Bool, test_fn::Nothing, julia_args::Cmd, test_args::Cmd, force_latest_compatible_version::Bool, allow_earlier_backwards_compatible_versions::Bool, allow_reresolve::Bool, kwargs::@Kwargs{io::IOContext{IO}}) @ Pkg.API /opt/julia/share/julia/stdlib/v1.14/Pkg/src/API.jl:572 [5] kwcall(::@NamedTuple{julia_args::Cmd, io::IOContext{IO}}, ::typeof(Pkg.API.test), ctx::Pkg.Types.Context, pkgs::Vector{PackageSpec}) @ Pkg.API /opt/julia/share/julia/stdlib/v1.14/Pkg/src/API.jl:548 [6] test(pkgs::Vector{PackageSpec}; io::IOContext{IO}, kwargs::@Kwargs{julia_args::Cmd}) @ Pkg.API /opt/julia/share/julia/stdlib/v1.14/Pkg/src/API.jl:172 [7] kwcall(::@NamedTuple{julia_args::Cmd}, ::typeof(Pkg.API.test), pkgs::Vector{PackageSpec}) @ Pkg.API /opt/julia/share/julia/stdlib/v1.14/Pkg/src/API.jl:161 [8] test(pkgs::Vector{String}; kwargs::@Kwargs{julia_args::Cmd}) @ Pkg.API /opt/julia/share/julia/stdlib/v1.14/Pkg/src/API.jl:160 [9] test @ /opt/julia/share/julia/stdlib/v1.14/Pkg/src/API.jl:160 [inlined] [10] kwcall(::@NamedTuple{julia_args::Cmd}, ::typeof(Pkg.API.test), pkg::String) @ Pkg.API /opt/julia/share/julia/stdlib/v1.14/Pkg/src/API.jl:159 [11] top-level scope @ /PkgEval.jl/scripts/evaluate.jl:237 [12] include(mod::Module, _path::String) @ Base ./Base.jl:309 [13] exec_options(opts::Base.JLOptions) @ Base ./client.jl:344 [14] _start() @ Base ./client.jl:577 in expression starting at /PkgEval.jl/scripts/evaluate.jl:228 PkgEval failed after 971.4s: package fails to precompile