Package evaluation to test StateSpaceModels on Julia 1.14.0-DEV.2114 (cccbcd9611*) started at 2026-05-05T13:09:33.703 ################################################################################ # Set-up # Installing PkgEval dependencies (TestEnv)... Activating project at `~/.julia/environments/v1.14` Set-up completed after 14.08s ################################################################################ # Installation # Installing StateSpaceModels... Resolving package versions... Updating `~/.julia/environments/v1.14/Project.toml` [99342f36] + StateSpaceModels v0.7.2 Updating `~/.julia/environments/v1.14/Manifest.toml` [47edcb42] + ADTypes v1.22.0 [79e6a3ab] + Adapt v4.5.2 [66dad0bd] + AliasTables v1.1.3 [4fba245c] + ArrayInterface v7.24.0 [bbf7d656] + CommonSubexpressions v0.3.1 [34da2185] + Compat v4.18.1 [187b0558] + ConstructionBase v1.6.0 [9a962f9c] + DataAPI v1.16.0 [864edb3b] + DataStructures v0.19.4 [163ba53b] + DiffResults v1.1.0 [b552c78f] + DiffRules v1.15.1 [a0c0ee7d] + DifferentiationInterface v0.7.17 [31c24e10] + Distributions v0.25.125 [ffbed154] + DocStringExtensions v0.9.5 [4e289a0a] + EnumX v1.0.7 [1a297f60] + FillArrays v1.16.0 [6a86dc24] + FiniteDiff v2.31.0 [f6369f11] + ForwardDiff v1.3.3 [34004b35] + HypergeometricFunctions v0.3.28 [92d709cd] + IrrationalConstants v0.2.6 [692b3bcd] + JLLWrappers v1.7.1 ⌃ [d3d80556] + LineSearches v7.5.1 [7a12625a] + LinearMaps v3.11.4 [2ab3a3ac] + LogExpFunctions v0.3.29 [1914dd2f] + MacroTools v0.5.16 [99c1a7ee] + MatrixEquations v2.5.6 [e1d29d7a] + Missings v1.2.0 ⌅ [d41bc354] + NLSolversBase v7.10.0 [77ba4419] + NaNMath v1.1.3 ⌅ [429524aa] + Optim v1.13.3 [bac558e1] + OrderedCollections v1.8.1 [90014a1f] + PDMats v0.11.37 [f27b6e38] + Polynomials v4.1.1 [85a6dd25] + PositiveFactorizations v0.2.4 [aea7be01] + PrecompileTools v1.3.3 [21216c6a] + Preferences v1.5.2 [43287f4e] + PtrArrays v1.4.0 [1fd47b50] + QuadGK v2.11.3 [3cdcf5f2] + RecipesBase v1.3.4 [189a3867] + Reexport v1.2.2 [ae029012] + Requires v1.3.1 [79098fc4] + Rmath v0.9.0 [42fb36cb] + SeasonalTrendLoess v0.1.0 [efcf1570] + Setfield v1.1.2 [1277b4bf] + ShiftedArrays v2.0.0 [a2af1166] + SortingAlgorithms v1.2.2 [276daf66] + SpecialFunctions v2.7.2 [99342f36] + StateSpaceModels v0.7.2 [1e83bf80] + StaticArraysCore v1.4.4 [10745b16] + Statistics v1.11.1 [82ae8749] + StatsAPI v1.8.0 [2913bbd2] + StatsBase v0.34.10 [4c63d2b9] + StatsFuns v1.5.2 [efe28fd5] + OpenSpecFun_jll v0.5.6+0 [f50d1b31] + Rmath_jll v0.5.1+0 [56f22d72] + Artifacts v1.11.0 [ade2ca70] + Dates v1.11.0 [8ba89e20] + Distributed v1.11.0 [9fa8497b] + Future v1.11.0 [8f399da3] + Libdl v1.11.0 [37e2e46d] + LinearAlgebra v1.13.0 [de0858da] + Printf 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 [4607b0f0] + SuiteSparse [fa267f1f] + TOML v1.0.3 [cf7118a7] + UUIDs v1.11.0 [4ec0a83e] + Unicode v1.11.0 [e66e0078] + CompilerSupportLibraries_jll v1.5.1+0 [4536629a] + OpenBLAS_jll v0.3.33+0 [05823500] + OpenLibm_jll v0.8.7+0 [bea87d4a] + SuiteSparse_jll v7.10.1+0 [8e850b90] + libblastrampoline_jll v5.15.0+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. To see why use `status --outdated -m` Installation completed after 6.11s ################################################################################ # Precompilation # Precompiling PkgEval dependencies... Precompiling package dependencies... Precompiling project... 9.1 s ✓ StateSpaceModels 1 dependency successfully precompiled in 12 seconds. 118 already precompiled. Precompilation completed after 37.89s ################################################################################ # Testing # Testing StateSpaceModels Status `/tmp/jl_amoR1R/Project.toml` [336ed68f] CSV v0.10.16 [a93c6f00] DataFrames v1.8.2 [31c24e10] Distributions v0.25.125 [99c1a7ee] MatrixEquations v2.5.6 ⌅ [429524aa] Optim v1.13.3 [bac558e1] OrderedCollections v1.8.1 [f27b6e38] Polynomials v4.1.1 [3cdcf5f2] RecipesBase v1.3.4 [42fb36cb] SeasonalTrendLoess v0.1.0 [1277b4bf] ShiftedArrays v2.0.0 [99342f36] StateSpaceModels v0.7.2 [10745b16] Statistics v1.11.1 [2913bbd2] StatsBase v0.34.10 [37e2e46d] LinearAlgebra v1.13.0 [de0858da] Printf v1.11.0 [9a3f8284] Random v1.11.0 [2f01184e] SparseArrays v1.13.0 [8dfed614] Test v1.11.0 Status `/tmp/jl_amoR1R/Manifest.toml` [47edcb42] ADTypes v1.22.0 [79e6a3ab] Adapt v4.5.2 [66dad0bd] AliasTables v1.1.3 [4fba245c] ArrayInterface v7.24.0 [336ed68f] CSV v0.10.16 [944b1d66] CodecZlib v0.7.8 [bbf7d656] CommonSubexpressions v0.3.1 [34da2185] Compat v4.18.1 [187b0558] ConstructionBase v1.6.0 [a8cc5b0e] Crayons v4.1.1 [9a962f9c] DataAPI v1.16.0 [a93c6f00] DataFrames v1.8.2 [864edb3b] DataStructures v0.19.4 [e2d170a0] DataValueInterfaces v1.0.0 [163ba53b] DiffResults v1.1.0 [b552c78f] DiffRules v1.15.1 [a0c0ee7d] DifferentiationInterface v0.7.17 [31c24e10] Distributions v0.25.125 [ffbed154] DocStringExtensions v0.9.5 [4e289a0a] EnumX v1.0.7 [48062228] FilePathsBase v0.9.24 [1a297f60] FillArrays v1.16.0 [6a86dc24] FiniteDiff v2.31.0 [f6369f11] ForwardDiff v1.3.3 [34004b35] HypergeometricFunctions v0.3.28 [842dd82b] InlineStrings v1.4.5 [41ab1584] InvertedIndices v1.3.1 [92d709cd] IrrationalConstants v0.2.6 [82899510] IteratorInterfaceExtensions v1.0.0 [692b3bcd] JLLWrappers v1.7.1 [b964fa9f] LaTeXStrings v1.4.0 ⌃ [d3d80556] LineSearches v7.5.1 [7a12625a] LinearMaps v3.11.4 [2ab3a3ac] LogExpFunctions v0.3.29 [1914dd2f] MacroTools v0.5.16 [99c1a7ee] MatrixEquations v2.5.6 [e1d29d7a] Missings v1.2.0 ⌅ [d41bc354] NLSolversBase v7.10.0 [77ba4419] NaNMath v1.1.3 ⌅ [429524aa] Optim v1.13.3 [bac558e1] OrderedCollections v1.8.1 [90014a1f] PDMats v0.11.37 [69de0a69] Parsers v2.8.4 [f27b6e38] Polynomials v4.1.1 [2dfb63ee] PooledArrays v1.4.3 [85a6dd25] PositiveFactorizations v0.2.4 [aea7be01] PrecompileTools v1.3.3 [21216c6a] Preferences v1.5.2 [08abe8d2] PrettyTables v3.3.2 [43287f4e] PtrArrays v1.4.0 [1fd47b50] QuadGK v2.11.3 [3cdcf5f2] RecipesBase v1.3.4 [189a3867] Reexport v1.2.2 [ae029012] Requires v1.3.1 [79098fc4] Rmath v0.9.0 [42fb36cb] SeasonalTrendLoess v0.1.0 [91c51154] SentinelArrays v1.4.9 [efcf1570] Setfield v1.1.2 [1277b4bf] ShiftedArrays v2.0.0 [a2af1166] SortingAlgorithms v1.2.2 [276daf66] SpecialFunctions v2.7.2 [99342f36] StateSpaceModels v0.7.2 [1e83bf80] StaticArraysCore v1.4.4 [10745b16] Statistics v1.11.1 [82ae8749] StatsAPI v1.8.0 [2913bbd2] StatsBase v0.34.10 [4c63d2b9] StatsFuns v1.5.2 [892a3eda] StringManipulation v0.4.4 [3783bdb8] TableTraits v1.0.1 [bd369af6] Tables v1.12.1 [3bb67fe8] TranscodingStreams v0.11.3 [ea10d353] WeakRefStrings v1.4.3 [76eceee3] WorkerUtilities v1.6.1 [efe28fd5] OpenSpecFun_jll v0.5.6+0 [f50d1b31] Rmath_jll v0.5.1+0 [56f22d72] Artifacts v1.11.0 [2a0f44e3] Base64 v1.11.0 [ade2ca70] Dates v1.11.0 [8ba89e20] Distributed v1.11.0 [7b1f6079] FileWatching v1.11.0 [9fa8497b] Future v1.11.0 [b77e0a4c] InteractiveUtils v1.11.0 [ac6e5ff7] JuliaSyntaxHighlighting v1.13.0 [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 [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 [8dfed614] Test v1.11.0 [cf7118a7] UUIDs v1.11.0 [4ec0a83e] Unicode v1.11.0 [e66e0078] CompilerSupportLibraries_jll v1.5.1+0 [4536629a] OpenBLAS_jll v0.3.33+0 [05823500] OpenLibm_jll v0.8.7+0 [bea87d4a] SuiteSparse_jll v7.10.1+0 [83775a58] Zlib_jll v1.3.2+0 [8e850b90] libblastrampoline_jll v5.15.0+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... Test Summary: | Pass Total Time Linear systems | 10 10 14.0s LocalLevel Results =============================================================== Model: LocalLevel Number of observations: 100 Number of unknown parameters: 2 Log-likelihood: -15.1399 AIC: 34.2797 AICc: 34.4034 BIC: 39.4901 --------------------------------------------------------------- Parameter Estimate Std.Error z stat p-value sigma2_ε 0.0748 0.0198 3.7706 0.0000 sigma2_η 0.0001 0.0097 0.0086 0.3809 SARIMA(1, 0, 0)x(0, 0, 0, 0) with zero mean Test Summary: | Total Time Prints | 0 28.3s Test Summary: | Pass Total Time LocalLevel | 142 142 1m18.8s Test Summary: | Pass Total Time Local Linear Trend Model | 4 4 14.6s ┌ Warning: The optimization process converged but the Hessian matrix is not positive definite. This means that StateSpaceModels.jl cannot estimate the distribution of the hyperparameters If you are interested in estimates of the distribution of ther hyperparameters we advise you to change the optimization algorithm by using the kwarg fit(...; optimizer = Optimizer(StateSpaceModels.Optim.THE_METHOD_OF_YOUR_CHOICE())) The list of possible algorithms can be found on this link https://julianlsolvers.github.io/Optim.jl/stable/# otherwise you can simply skip this proccess by using fit(...; save_hyperparameter_distribution=false) └ @ StateSpaceModels ~/.julia/packages/StateSpaceModels/bezQE/src/fit.jl:57 Test Summary: | Pass Total Time Local Level With Cycle Model | 7 7 5.3s ┌ Warning: The optimization process converged but the Hessian matrix is not positive definite. This means that StateSpaceModels.jl cannot estimate the distribution of the hyperparameters If you are interested in estimates of the distribution of ther hyperparameters we advise you to change the optimization algorithm by using the kwarg fit(...; optimizer = Optimizer(StateSpaceModels.Optim.THE_METHOD_OF_YOUR_CHOICE())) The list of possible algorithms can be found on this link https://julianlsolvers.github.io/Optim.jl/stable/# otherwise you can simply skip this proccess by using fit(...; save_hyperparameter_distribution=false) └ @ StateSpaceModels ~/.julia/packages/StateSpaceModels/bezQE/src/fit.jl:57 Test Summary: | Pass Total Time Local Level With Explanatory Model | 2 2 7.8s Test Summary: | Pass Total Time Basic Structural Model | 25 25 17.7s ┌ Warning: The optimization process converged but the Hessian matrix is not positive definite. This means that StateSpaceModels.jl cannot estimate the distribution of the hyperparameters If you are interested in estimates of the distribution of ther hyperparameters we advise you to change the optimization algorithm by using the kwarg fit(...; optimizer = Optimizer(StateSpaceModels.Optim.THE_METHOD_OF_YOUR_CHOICE())) The list of possible algorithms can be found on this link https://julianlsolvers.github.io/Optim.jl/stable/# otherwise you can simply skip this proccess by using fit(...; save_hyperparameter_distribution=false) └ @ StateSpaceModels ~/.julia/packages/StateSpaceModels/bezQE/src/fit.jl:57 ┌ Warning: The optimization process converged but the Hessian matrix is not positive definite. This means that StateSpaceModels.jl cannot estimate the distribution of the hyperparameters If you are interested in estimates of the distribution of ther hyperparameters we advise you to change the optimization algorithm by using the kwarg fit(...; optimizer = Optimizer(StateSpaceModels.Optim.THE_METHOD_OF_YOUR_CHOICE())) The list of possible algorithms can be found on this link https://julianlsolvers.github.io/Optim.jl/stable/# otherwise you can simply skip this proccess by using fit(...; save_hyperparameter_distribution=false) └ @ StateSpaceModels ~/.julia/packages/StateSpaceModels/bezQE/src/fit.jl:57 forec = forecast(model, ones(10, 2)) = StateSpaceModels.Forecast{Float64}([[6.074603990872448], [6.108957550986132], [6.11581902173328], [6.139580332225014], [6.143463776641276], [6.127542064913756], [6.121072245848277], [6.131986281299225], [6.135706983735872], [6.161930481423012]], [[0.01284492738343094;;], [0.012844927319166161;;], [0.025689854760130283;;], [0.03853478224265534;;], [0.05137970971557432;;], [0.06422463712774067;;], [0.07706956458637247;;], [0.08991449203813907;;], [0.10270233084350175;;], [0.11549016943261727;;]]) Test Summary: | Pass Total Time Basic Structural With Explanatory Model | 23 23 14.1s ┌ Warning: The optimization process converged but the Hessian matrix is not positive definite. This means that StateSpaceModels.jl cannot estimate the distribution of the hyperparameters If you are interested in estimates of the distribution of ther hyperparameters we advise you to change the optimization algorithm by using the kwarg fit(...; optimizer = Optimizer(StateSpaceModels.Optim.THE_METHOD_OF_YOUR_CHOICE())) The list of possible algorithms can be found on this link https://julianlsolvers.github.io/Optim.jl/stable/# otherwise you can simply skip this proccess by using fit(...; save_hyperparameter_distribution=false) └ @ StateSpaceModels ~/.julia/packages/StateSpaceModels/bezQE/src/fit.jl:57 Test Summary: | Pass Total Time Multivariate Basic Structural Model | 11 11 41.5s ┌ Warning: The optimization process converged but the Hessian matrix is not positive definite. This means that StateSpaceModels.jl cannot estimate the distribution of the hyperparameters If you are interested in estimates of the distribution of ther hyperparameters we advise you to change the optimization algorithm by using the kwarg fit(...; optimizer = Optimizer(StateSpaceModels.Optim.THE_METHOD_OF_YOUR_CHOICE())) The list of possible algorithms can be found on this link https://julianlsolvers.github.io/Optim.jl/stable/# otherwise you can simply skip this proccess by using fit(...; save_hyperparameter_distribution=false) └ @ StateSpaceModels ~/.julia/packages/StateSpaceModels/bezQE/src/fit.jl:57 Model specification Selection metric SARIMA(2, 1, 2)x(0, 0, 0, 0) with non-zero mean : 1273.7594422205827 SARIMA(1, 1, 0)x(0, 0, 0, 0) with non-zero mean : 1283.7664413377438 SARIMA(0, 1, 1)x(0, 0, 0, 0) with non-zero mean : 1271.3254393136017 SARIMA(0, 1, 0)x(0, 0, 0, 0) with non-zero mean : 1298.82084537551 Search iteration complete: Current best is SARIMA(0, 1, 1)x(0, 0, 0, 0) with non-zero mean SARIMA(0, 1, 1)x(0, 0, 0, 0) with non-zero mean : 1271.3254393136017 SARIMA(0, 1, 2)x(0, 0, 0, 0) with non-zero mean : 1270.340103163738 SARIMA(1, 1, 1)x(0, 0, 0, 0) with non-zero mean : 1269.6406822029103 SARIMA(1, 1, 2)x(0, 0, 0, 0) with non-zero mean : 1271.5243197020661 SARIMA(0, 1, 1)x(0, 0, 0, 0) with zero mean : 1269.1991228342006 Search iteration complete: Current best is SARIMA(0, 1, 1)x(0, 0, 0, 0) with zero mean SARIMA(0, 1, 1)x(0, 0, 0, 0) with zero mean : 1269.1991228342006 SARIMA(0, 1, 0)x(0, 0, 0, 0) with zero mean : 1296.7379503618345 SARIMA(0, 1, 2)x(0, 0, 0, 0) with zero mean : 1268.1691182508343 SARIMA(1, 1, 0)x(0, 0, 0, 0) with zero mean : 1281.639997648152 SARIMA(1, 1, 1)x(0, 0, 0, 0) with zero mean : 1267.4696939431421 SARIMA(1, 1, 2)x(0, 0, 0, 0) with zero mean : 1269.3071444814511 Search iteration complete: Current best is SARIMA(1, 1, 1)x(0, 0, 0, 0) with zero mean SARIMA(1, 1, 1)x(0, 0, 0, 0) with zero mean : 1267.4696939431421 SARIMA(2, 1, 0)x(0, 0, 0, 0) with zero mean : 1277.6748597747246 SARIMA(2, 1, 1)x(0, 0, 0, 0) with zero mean : 1269.2858066438546 SARIMA(2, 1, 2)x(0, 0, 0, 0) with zero mean : 1271.494573482016 Search iteration complete: Current best is SARIMA(1, 1, 1)x(0, 0, 0, 0) with zero mean Model specification Selection metric SARIMA(2, 0, 2)x(1, 1, 1, 12) with non-zero mean : -454.0885896781967 SARIMA(1, 0, 0)x(1, 1, 0, 12) with non-zero mean : 2.88e22 SARIMA(0, 0, 1)x(0, 1, 1, 12) with non-zero mean : -276.0100119759103 SARIMA(0, 0, 0)x(0, 1, 0, 12) with non-zero mean : -150.6710081764367 Search iteration complete: Current best is SARIMA(2, 0, 2)x(1, 1, 1, 12) with non-zero mean SARIMA(2, 0, 2)x(1, 1, 1, 12) with non-zero mean : -454.0885896781967 SARIMA(1, 0, 1)x(1, 1, 1, 12) with non-zero mean : 2.88e22 SARIMA(1, 0, 2)x(1, 1, 1, 12) with non-zero mean : 2.88e22 SARIMA(1, 0, 3)x(1, 1, 1, 12) with non-zero mean : 2.88e22 SARIMA(2, 0, 1)x(1, 1, 1, 12) with non-zero mean : -476.7792724034359 SARIMA(2, 0, 3)x(1, 1, 1, 12) with non-zero mean : 2.88e22 SARIMA(3, 0, 1)x(1, 1, 1, 12) with non-zero mean : 2.88e22 SARIMA(3, 0, 2)x(1, 1, 1, 12) with non-zero mean : -463.1232472863847 SARIMA(2, 0, 2)x(0, 1, 0, 12) with non-zero mean : -441.77865134755933 SARIMA(2, 0, 2)x(0, 1, 1, 12) with non-zero mean : -476.95692627250355 SARIMA(2, 0, 2)x(0, 1, 2, 12) with non-zero mean : -475.3819309761346 SARIMA(2, 0, 2)x(1, 1, 0, 12) with non-zero mean : -443.5234601131388 SARIMA(2, 0, 2)x(1, 1, 2, 12) with non-zero mean : -436.1710378467289 SARIMA(2, 0, 2)x(2, 1, 0, 12) with non-zero mean : -443.0873732761951 SARIMA(2, 0, 2)x(2, 1, 1, 12) with non-zero mean : -475.3322503650885 SARIMA(2, 0, 2)x(2, 1, 2, 12) with non-zero mean : -471.685919055935 SARIMA(2, 0, 2)x(1, 1, 1, 12) with zero mean : -457.67703987149713 Search iteration complete: Current best is SARIMA(2, 0, 2)x(0, 1, 1, 12) with non-zero mean SARIMA(2, 0, 2)x(0, 1, 1, 12) with non-zero mean : -476.95692627250355 SARIMA(1, 0, 1)x(0, 1, 1, 12) with non-zero mean : -480.67332946613703 SARIMA(1, 0, 2)x(0, 1, 1, 12) with non-zero mean : -478.6768198795179 SARIMA(1, 0, 3)x(0, 1, 1, 12) with non-zero mean : -479.43004884229595 SARIMA(2, 0, 1)x(0, 1, 1, 12) with non-zero mean : -478.91265786707834 SARIMA(2, 0, 3)x(0, 1, 1, 12) with non-zero mean : -474.56007065855744 SARIMA(3, 0, 1)x(0, 1, 1, 12) with non-zero mean : -474.9452568412965 SARIMA(3, 0, 2)x(0, 1, 1, 12) with non-zero mean : -476.10517879678594 SARIMA(2, 0, 2)x(0, 1, 1, 12) with zero mean : -479.16620912767115 Search iteration complete: Current best is SARIMA(1, 0, 1)x(0, 1, 1, 12) with non-zero mean SARIMA(1, 0, 1)x(0, 1, 1, 12) with non-zero mean : -480.67332946613703 SARIMA(0, 0, 0)x(0, 1, 1, 12) with non-zero mean : -195.25435443204407 SARIMA(0, 0, 2)x(0, 1, 1, 12) with non-zero mean : -342.1480313198996 SARIMA(1, 0, 0)x(0, 1, 1, 12) with non-zero mean : -465.26465355070144 SARIMA(2, 0, 0)x(0, 1, 1, 12) with non-zero mean : -453.4270065805327 SARIMA(1, 0, 1)x(0, 1, 0, 12) with non-zero mean : -449.2867420993558 SARIMA(1, 0, 1)x(0, 1, 2, 12) with non-zero mean : -479.0576731341482 SARIMA(1, 0, 1)x(1, 1, 0, 12) with non-zero mean : 2.88e22 SARIMA(1, 0, 1)x(1, 1, 2, 12) with non-zero mean : 2.88e22 SARIMA(1, 0, 1)x(0, 1, 1, 12) with zero mean : -482.82034250367616 Search iteration complete: Current best is SARIMA(1, 0, 1)x(0, 1, 1, 12) with zero mean SARIMA(1, 0, 1)x(0, 1, 1, 12) with zero mean : -482.82034250367616 SARIMA(0, 0, 0)x(0, 1, 1, 12) with zero mean : -197.34067664448258 SARIMA(0, 0, 1)x(0, 1, 1, 12) with zero mean : -278.12635321284887 SARIMA(0, 0, 2)x(0, 1, 1, 12) with zero mean : -344.29504416679123 SARIMA(1, 0, 0)x(0, 1, 1, 12) with zero mean : -467.38099494824894 SARIMA(1, 0, 2)x(0, 1, 1, 12) with zero mean : -480.8551761743883 SARIMA(2, 0, 0)x(0, 1, 1, 12) with zero mean : -455.57409154187206 SARIMA(2, 0, 1)x(0, 1, 1, 12) with zero mean : -468.14739345077993 SARIMA(1, 0, 1)x(0, 1, 0, 12) with zero mean : -451.4030834021758 SARIMA(1, 0, 1)x(0, 1, 2, 12) with zero mean : -481.23602562047114 SARIMA(1, 0, 1)x(1, 1, 0, 12) with zero mean : 2.88e22 SARIMA(1, 0, 1)x(1, 1, 1, 12) with zero mean : 2.88e22 SARIMA(1, 0, 1)x(1, 1, 2, 12) with zero mean : 2.88e22 Search iteration complete: Current best is SARIMA(1, 0, 1)x(0, 1, 1, 12) with zero mean Test Summary: | Pass Broken Total Time SARIMA | 44 2 46 7m50.1s ┌ Warning: The optimization process converged but the Hessian matrix is not positive definite. This means that StateSpaceModels.jl cannot estimate the distribution of the hyperparameters If you are interested in estimates of the distribution of ther hyperparameters we advise you to change the optimization algorithm by using the kwarg fit(...; optimizer = Optimizer(StateSpaceModels.Optim.THE_METHOD_OF_YOUR_CHOICE())) The list of possible algorithms can be found on this link https://julianlsolvers.github.io/Optim.jl/stable/# otherwise you can simply skip this proccess by using fit(...; save_hyperparameter_distribution=false) └ @ StateSpaceModels ~/.julia/packages/StateSpaceModels/bezQE/src/fit.jl:57 Test Summary: | Pass Total Time UnobservedComponents | 13 13 9.4s ┌ Warning: The optimization process converged but the Hessian matrix is not positive definite. This means that StateSpaceModels.jl cannot estimate the distribution of the hyperparameters If you are interested in estimates of the distribution of ther hyperparameters we advise you to change the optimization algorithm by using the kwarg fit(...; optimizer = Optimizer(StateSpaceModels.Optim.THE_METHOD_OF_YOUR_CHOICE())) The list of possible algorithms can be found on this link https://julianlsolvers.github.io/Optim.jl/stable/# otherwise you can simply skip this proccess by using fit(...; save_hyperparameter_distribution=false) └ @ StateSpaceModels ~/.julia/packages/StateSpaceModels/bezQE/src/fit.jl:57 ┌ Warning: The optimization process converged but the Hessian matrix is not positive definite. This means that StateSpaceModels.jl cannot estimate the distribution of the hyperparameters If you are interested in estimates of the distribution of ther hyperparameters we advise you to change the optimization algorithm by using the kwarg fit(...; optimizer = Optimizer(StateSpaceModels.Optim.THE_METHOD_OF_YOUR_CHOICE())) The list of possible algorithms can be found on this link https://julianlsolvers.github.io/Optim.jl/stable/# otherwise you can simply skip this proccess by using fit(...; save_hyperparameter_distribution=false) └ @ StateSpaceModels ~/.julia/packages/StateSpaceModels/bezQE/src/fit.jl:57 ┌ Warning: The optimization process converged but the Hessian matrix is not positive definite. This means that StateSpaceModels.jl cannot estimate the distribution of the hyperparameters If you are interested in estimates of the distribution of ther hyperparameters we advise you to change the optimization algorithm by using the kwarg fit(...; optimizer = Optimizer(StateSpaceModels.Optim.THE_METHOD_OF_YOUR_CHOICE())) The list of possible algorithms can be found on this link https://julianlsolvers.github.io/Optim.jl/stable/# otherwise you can simply skip this proccess by using fit(...; save_hyperparameter_distribution=false) └ @ StateSpaceModels ~/.julia/packages/StateSpaceModels/bezQE/src/fit.jl:57 Test Summary: | Pass Total Time UnobservedComponentsExplanatory | 29 29 11.6s Test Summary: | Pass Total Time Regression | 51 51 4.4s ┌ Warning: The optimization process converged but the Hessian matrix is not positive definite. This means that StateSpaceModels.jl cannot estimate the distribution of the hyperparameters If you are interested in estimates of the distribution of ther hyperparameters we advise you to change the optimization algorithm by using the kwarg fit(...; optimizer = Optimizer(StateSpaceModels.Optim.THE_METHOD_OF_YOUR_CHOICE())) The list of possible algorithms can be found on this link https://julianlsolvers.github.io/Optim.jl/stable/# otherwise you can simply skip this proccess by using fit(...; save_hyperparameter_distribution=false) └ @ StateSpaceModels ~/.julia/packages/StateSpaceModels/bezQE/src/fit.jl:57 ┌ Warning: The optimization process converged but the Hessian matrix is not positive definite. This means that StateSpaceModels.jl cannot estimate the distribution of the hyperparameters If you are interested in estimates of the distribution of ther hyperparameters we advise you to change the optimization algorithm by using the kwarg fit(...; optimizer = Optimizer(StateSpaceModels.Optim.THE_METHOD_OF_YOUR_CHOICE())) The list of possible algorithms can be found on this link https://julianlsolvers.github.io/Optim.jl/stable/# otherwise you can simply skip this proccess by using fit(...; save_hyperparameter_distribution=false) └ @ StateSpaceModels ~/.julia/packages/StateSpaceModels/bezQE/src/fit.jl:57 ┌ Warning: The optimization process converged but the Hessian matrix is not positive definite. This means that StateSpaceModels.jl cannot estimate the distribution of the hyperparameters If you are interested in estimates of the distribution of ther hyperparameters we advise you to change the optimization algorithm by using the kwarg fit(...; optimizer = Optimizer(StateSpaceModels.Optim.THE_METHOD_OF_YOUR_CHOICE())) The list of possible algorithms can be found on this link https://julianlsolvers.github.io/Optim.jl/stable/# otherwise you can simply skip this proccess by using fit(...; save_hyperparameter_distribution=false) └ @ StateSpaceModels ~/.julia/packages/StateSpaceModels/bezQE/src/fit.jl:57 ┌ Warning: The optimization process converged but the Hessian matrix is not positive definite. This means that StateSpaceModels.jl cannot estimate the distribution of the hyperparameters If you are interested in estimates of the distribution of ther hyperparameters we advise you to change the optimization algorithm by using the kwarg fit(...; optimizer = Optimizer(StateSpaceModels.Optim.THE_METHOD_OF_YOUR_CHOICE())) The list of possible algorithms can be found on this link https://julianlsolvers.github.io/Optim.jl/stable/# otherwise you can simply skip this proccess by using fit(...; save_hyperparameter_distribution=false) └ @ StateSpaceModels ~/.julia/packages/StateSpaceModels/bezQE/src/fit.jl:57 ┌ Warning: The optimization process converged but the Hessian matrix is not positive definite. This means that StateSpaceModels.jl cannot estimate the distribution of the hyperparameters If you are interested in estimates of the distribution of ther hyperparameters we advise you to change the optimization algorithm by using the kwarg fit(...; optimizer = Optimizer(StateSpaceModels.Optim.THE_METHOD_OF_YOUR_CHOICE())) The list of possible algorithms can be found on this link https://julianlsolvers.github.io/Optim.jl/stable/# otherwise you can simply skip this proccess by using fit(...; save_hyperparameter_distribution=false) └ @ StateSpaceModels ~/.julia/packages/StateSpaceModels/bezQE/src/fit.jl:57 ┌ Warning: The optimization process converged but the Hessian matrix is not positive definite. This means that StateSpaceModels.jl cannot estimate the distribution of the hyperparameters If you are interested in estimates of the distribution of ther hyperparameters we advise you to change the optimization algorithm by using the kwarg fit(...; optimizer = Optimizer(StateSpaceModels.Optim.THE_METHOD_OF_YOUR_CHOICE())) The list of possible algorithms can be found on this link https://julianlsolvers.github.io/Optim.jl/stable/# otherwise you can simply skip this proccess by using fit(...; save_hyperparameter_distribution=false) └ @ StateSpaceModels ~/.julia/packages/StateSpaceModels/bezQE/src/fit.jl:57 Test Summary: | Pass Total Time ExponentialSmoothing | 14 14 13.0s CrossValidation: step 1 of 20 CrossValidation: step 2 of 20 CrossValidation: step 3 of 20 CrossValidation: step 4 of 20 CrossValidation: step 5 of 20 CrossValidation: step 6 of 20 CrossValidation: step 7 of 20 CrossValidation: step 8 of 20 CrossValidation: step 9 of 20 CrossValidation: step 10 of 20 CrossValidation: step 11 of 20 CrossValidation: step 12 of 20 CrossValidation: step 13 of 20 CrossValidation: step 14 of 20 CrossValidation: step 15 of 20 CrossValidation: step 16 of 20 CrossValidation: step 17 of 20 CrossValidation: step 18 of 20 CrossValidation: step 19 of 20 CrossValidation: step 20 of 20 Test Summary: | Pass Total Time Naive models | 13 13 4.9s Test Summary: | Pass Total Time DAR Model | 4 4 13.3s Test Summary: | Pass Total Time Vehicle tracking | 1 1 1.1s Test Summary: | Pass Total Time Visualization Forecast | 4 4 2.5s ┌ Warning: The optimization process converged but the Hessian matrix is not positive definite. This means that StateSpaceModels.jl cannot estimate the distribution of the hyperparameters If you are interested in estimates of the distribution of ther hyperparameters we advise you to change the optimization algorithm by using the kwarg fit(...; optimizer = Optimizer(StateSpaceModels.Optim.THE_METHOD_OF_YOUR_CHOICE())) The list of possible algorithms can be found on this link https://julianlsolvers.github.io/Optim.jl/stable/# otherwise you can simply skip this proccess by using fit(...; save_hyperparameter_distribution=false) └ @ StateSpaceModels ~/.julia/packages/StateSpaceModels/bezQE/src/fit.jl:57 Test Summary: | Pass Total Time Visualization Unobserved Components | 8 8 7.3s CrossValidation: step 1 of 10 CrossValidation: step 2 of 10 CrossValidation: step 3 of 10 CrossValidation: step 4 of 10 CrossValidation: step 5 of 10 CrossValidation: step 6 of 10 CrossValidation: step 7 of 10 CrossValidation: step 8 of 10 CrossValidation: step 9 of 10 CrossValidation: step 10 of 10 Test Summary: | Pass Total Time Visualization Forecast | 1 1 11.3s Test Summary: | Pass Total Time Visualization Diagnostics | 4 4 0.6s Testing StateSpaceModels tests passed Testing completed after 819.37s PkgEval succeeded after 894.21s