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Results with Julia v1.2.0
Testing was successful .
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Resolving package versions...
Installed Missings ──────────────────── v0.4.3
Installed DataAPI ───────────────────── v1.1.0
Installed PDMats ────────────────────── v0.9.10
Installed TableTraits ───────────────── v1.0.0
Installed AbstractFFTs ──────────────── v0.5.0
Installed HurdleDMR ─────────────────── v1.3.0
Installed BinaryProvider ────────────── v0.5.8
Installed StatsBase ─────────────────── v0.32.0
Installed Conda ─────────────────────── v1.3.0
Installed StatsFuns ─────────────────── v0.9.0
Installed URIParser ─────────────────── v0.4.0
Installed DataValueInterfaces ───────── v1.0.0
Installed Reexport ──────────────────── v0.2.0
Installed Compat ────────────────────── v2.2.0
Installed Polynomials ───────────────── v0.6.0
Installed Rmath ─────────────────────── v0.5.1
Installed OrderedCollections ────────── v1.1.0
Installed IterTools ─────────────────── v1.3.0
Installed Tables ────────────────────── v0.2.11
Installed GLM ───────────────────────── v1.3.4
Installed LambertW ──────────────────── v0.4.3
Installed ShiftedArrays ─────────────── v1.0.0
Installed RecipesBase ───────────────── v0.7.0
Installed DataStructures ────────────── v0.17.6
Installed Distributions ─────────────── v0.21.9
Installed StatsModels ───────────────── v0.6.7
Installed Parsers ───────────────────── v0.3.10
Installed JSON ──────────────────────── v0.21.0
Installed FFTW ──────────────────────── v1.1.0
Installed IteratorInterfaceExtensions ─ v1.0.0
Installed QuadGK ────────────────────── v2.1.1
Installed DSP ───────────────────────── v0.6.2
Installed Lasso ─────────────────────── v0.5.0
Installed SortingAlgorithms ─────────── v0.3.1
Installed LoggingExtras ─────────────── v0.3.0
Installed VersionParsing ────────────── v1.1.3
Installed SpecialFunctions ──────────── v0.8.0
Installed BinDeps ───────────────────── v0.8.10
Installed MLBase ────────────────────── v0.8.0
Installed Arpack ────────────────────── v0.3.1
Updating `~/.julia/environments/v1.2/Project.toml`
[f9e53bcf] + HurdleDMR v1.3.0
Updating `~/.julia/environments/v1.2/Manifest.toml`
[621f4979] + AbstractFFTs v0.5.0
[7d9fca2a] + Arpack v0.3.1
[9e28174c] + BinDeps v0.8.10
[b99e7846] + BinaryProvider v0.5.8
[34da2185] + Compat v2.2.0
[8f4d0f93] + Conda v1.3.0
[717857b8] + DSP v0.6.2
[9a962f9c] + DataAPI v1.1.0
[864edb3b] + DataStructures v0.17.6
[e2d170a0] + DataValueInterfaces v1.0.0
[31c24e10] + Distributions v0.21.9
[7a1cc6ca] + FFTW v1.1.0
[38e38edf] + GLM v1.3.4
[f9e53bcf] + HurdleDMR v1.3.0
[c8e1da08] + IterTools v1.3.0
[82899510] + IteratorInterfaceExtensions v1.0.0
[682c06a0] + JSON v0.21.0
[984bce1d] + LambertW v0.4.3
[b4fcebef] + Lasso v0.5.0
[e6f89c97] + LoggingExtras v0.3.0
[f0e99cf1] + MLBase v0.8.0
[e1d29d7a] + Missings v0.4.3
[bac558e1] + OrderedCollections v1.1.0
[90014a1f] + PDMats v0.9.10
[69de0a69] + Parsers v0.3.10
[f27b6e38] + Polynomials v0.6.0
[1fd47b50] + QuadGK v2.1.1
[3cdcf5f2] + RecipesBase v0.7.0
[189a3867] + Reexport v0.2.0
[79098fc4] + Rmath v0.5.1
[1277b4bf] + ShiftedArrays v1.0.0
[a2af1166] + SortingAlgorithms v0.3.1
[276daf66] + SpecialFunctions v0.8.0
[2913bbd2] + StatsBase v0.32.0
[4c63d2b9] + StatsFuns v0.9.0
[3eaba693] + StatsModels v0.6.7
[3783bdb8] + TableTraits v1.0.0
[bd369af6] + Tables v0.2.11
[30578b45] + URIParser v0.4.0
[81def892] + VersionParsing v1.1.3
[2a0f44e3] + Base64
[ade2ca70] + Dates
[8bb1440f] + DelimitedFiles
[8ba89e20] + Distributed
[b77e0a4c] + InteractiveUtils
[76f85450] + LibGit2
[8f399da3] + Libdl
[37e2e46d] + LinearAlgebra
[56ddb016] + Logging
[d6f4376e] + Markdown
[a63ad114] + Mmap
[44cfe95a] + Pkg
[de0858da] + Printf
[3fa0cd96] + REPL
[9a3f8284] + Random
[ea8e919c] + SHA
[9e88b42a] + Serialization
[1a1011a3] + SharedArrays
[6462fe0b] + Sockets
[2f01184e] + SparseArrays
[10745b16] + Statistics
[4607b0f0] + SuiteSparse
[8dfed614] + Test
[cf7118a7] + UUIDs
[4ec0a83e] + Unicode
Building Conda ───────────→ `~/.julia/packages/Conda/kLXeC/deps/build.log`
Building Rmath ───────────→ `~/.julia/packages/Rmath/4wt82/deps/build.log`
Building FFTW ────────────→ `~/.julia/packages/FFTW/loJ3F/deps/build.log`
Building SpecialFunctions → `~/.julia/packages/SpecialFunctions/ne2iw/deps/build.log`
Building Arpack ──────────→ `~/.julia/packages/Arpack/cu5By/deps/build.log`
Testing HurdleDMR
Resolving package versions...
Installed PooledArrays ────── v0.5.2
Installed ArrayLayouts ────── v0.1.5
Installed FillArrays ──────── v0.8.2
Installed FilePathsBase ───── v0.7.0
Installed DataFrames ──────── v0.19.4
Installed WeakRefStrings ──── v0.6.1
Installed InvertedIndices ─── v1.0.0
Installed CategoricalArrays ─ v0.7.3
Installed StaticArrays ────── v0.12.1
Installed LazyArrays ──────── v0.14.10
Installed MacroTools ──────── v0.5.2
Installed CSV ─────────────── v0.5.18
Status `/tmp/jl_Rr48pt/Manifest.toml`
[621f4979] AbstractFFTs v0.5.0
[7d9fca2a] Arpack v0.3.1
[4c555306] ArrayLayouts v0.1.5
[9e28174c] BinDeps v0.8.10
[b99e7846] BinaryProvider v0.5.8
[336ed68f] CSV v0.5.18
[324d7699] CategoricalArrays v0.7.3
[34da2185] Compat v2.2.0
[8f4d0f93] Conda v1.3.0
[717857b8] DSP v0.6.2
[9a962f9c] DataAPI v1.1.0
[a93c6f00] DataFrames v0.19.4
[864edb3b] DataStructures v0.17.6
[e2d170a0] DataValueInterfaces v1.0.0
[31c24e10] Distributions v0.21.9
[7a1cc6ca] FFTW v1.1.0
[48062228] FilePathsBase v0.7.0
[1a297f60] FillArrays v0.8.2
[38e38edf] GLM v1.3.4
[f9e53bcf] HurdleDMR v1.3.0
[41ab1584] InvertedIndices v1.0.0
[c8e1da08] IterTools v1.3.0
[82899510] IteratorInterfaceExtensions v1.0.0
[682c06a0] JSON v0.21.0
[984bce1d] LambertW v0.4.3
[b4fcebef] Lasso v0.5.0
[5078a376] LazyArrays v0.14.10
[e6f89c97] LoggingExtras v0.3.0
[f0e99cf1] MLBase v0.8.0
[1914dd2f] MacroTools v0.5.2
[e1d29d7a] Missings v0.4.3
[bac558e1] OrderedCollections v1.1.0
[90014a1f] PDMats v0.9.10
[69de0a69] Parsers v0.3.10
[f27b6e38] Polynomials v0.6.0
[2dfb63ee] PooledArrays v0.5.2
[1fd47b50] QuadGK v2.1.1
[3cdcf5f2] RecipesBase v0.7.0
[189a3867] Reexport v0.2.0
[79098fc4] Rmath v0.5.1
[1277b4bf] ShiftedArrays v1.0.0
[a2af1166] SortingAlgorithms v0.3.1
[276daf66] SpecialFunctions v0.8.0
[90137ffa] StaticArrays v0.12.1
[2913bbd2] StatsBase v0.32.0
[4c63d2b9] StatsFuns v0.9.0
[3eaba693] StatsModels v0.6.7
[3783bdb8] TableTraits v1.0.0
[bd369af6] Tables v0.2.11
[30578b45] URIParser v0.4.0
[81def892] VersionParsing v1.1.3
[ea10d353] WeakRefStrings v0.6.1
[2a0f44e3] Base64 [`@stdlib/Base64`]
[ade2ca70] Dates [`@stdlib/Dates`]
[8bb1440f] DelimitedFiles [`@stdlib/DelimitedFiles`]
[8ba89e20] Distributed [`@stdlib/Distributed`]
[9fa8497b] Future [`@stdlib/Future`]
[b77e0a4c] InteractiveUtils [`@stdlib/InteractiveUtils`]
[76f85450] LibGit2 [`@stdlib/LibGit2`]
[8f399da3] Libdl [`@stdlib/Libdl`]
[37e2e46d] LinearAlgebra [`@stdlib/LinearAlgebra`]
[56ddb016] Logging [`@stdlib/Logging`]
[d6f4376e] Markdown [`@stdlib/Markdown`]
[a63ad114] Mmap [`@stdlib/Mmap`]
[44cfe95a] Pkg [`@stdlib/Pkg`]
[de0858da] Printf [`@stdlib/Printf`]
[3fa0cd96] REPL [`@stdlib/REPL`]
[9a3f8284] Random [`@stdlib/Random`]
[ea8e919c] SHA [`@stdlib/SHA`]
[9e88b42a] Serialization [`@stdlib/Serialization`]
[1a1011a3] SharedArrays [`@stdlib/SharedArrays`]
[6462fe0b] Sockets [`@stdlib/Sockets`]
[2f01184e] SparseArrays [`@stdlib/SparseArrays`]
[10745b16] Statistics [`@stdlib/Statistics`]
[4607b0f0] SuiteSparse [`@stdlib/SuiteSparse`]
[8dfed614] Test [`@stdlib/Test`]
[cf7118a7] UUIDs [`@stdlib/UUIDs`]
[4ec0a83e] Unicode [`@stdlib/Unicode`]
[ Info: Starting 4 parallel workers for tests...
[ Info: 4 parallel workers started
[ Info: Testing hurdle degenerate cases. The following warnings about step-halving are expected ...
1: λ=0.000386732571607375, pct_dev=6.491976604627858e-6
2: λ=0.00035237631582540674, pct_dev=0.004137275679515495
step-halving because obj=0.004873710484493199 > 0.0048737104844521545 + 5.348152476436496e-15 = length(scratchmu)*eps(objold)
3: λ=0.0003210721751172995, pct_dev=0.007781659027663257
4: λ=0.00029254900799187346, pct_dev=0.011000893812644796
5: λ=0.00026655976042072805, pct_dev=0.01384672457319358
6: λ=0.00024287932597443493, pct_dev=0.01636328834963452
step-halving because obj=0.004853629958394753 > 0.00485362995832963 + 5.348152476436496e-15 = length(scratchmu)*eps(objold)
7: λ=0.00022130259605833834, pct_dev=0.018588564316925682
step-halving because obj=0.004847225402105616 > 0.004847225402075316 + 5.348152476436496e-15 = length(scratchmu)*eps(objold)
8: λ=0.00020164268336002862, pct_dev=0.020555493976648687
step-halving because obj=0.004840589108480022 > 0.004840589108449965 + 5.348152476436496e-15 = length(scratchmu)*eps(objold)
9: λ=0.00018372930312084647, pct_dev=0.022292855685093316
10: λ=0.00016740729821076853, pct_dev=0.023825953055227722
11: λ=0.00015253529523157167, pct_dev=0.02517716069551157
12: λ=0.0001389844800080886, pct_dev=0.026366360317267468
13: λ=0.00012663748186144804, pct_dev=0.027411290020289636
14: λ=0.00011538735700040242, pct_dev=0.02832782749366669
15: λ=0.00010513666222536851, pct_dev=0.029130219588688777
step-halving because obj=0.0047950177502431605 > 0.004795017750074621 + 5.348152476436496e-15 = length(scratchmu)*eps(objold)
16: λ=9.579661092204997e-5, pct_dev=0.029831270237958174
step-halving because obj=0.004789253164598393 > 0.004789253164442045 + 5.348152476436496e-15 = length(scratchmu)*eps(objold)
17: λ=8.728630403425833e-5, pct_dev=0.030442496928184237
step-halving because obj=0.004783753703245748 > 0.004783753703178281 + 5.348152476436496e-15 = length(scratchmu)*eps(objold)
18: λ=7.953202935498933e-5, pct_dev=0.030974261196463515
19: λ=7.246662306655003e-5, pct_dev=0.031435879206021755
20: λ=6.60288879997001e-5, pct_dev=0.03183571788072681
21: λ=6.016306357304766e-5, pct_dev=0.03218127930818637
step-halving because obj=0.004764518539996998 > 0.004764518539672642 + 5.348152476436496e-15 = length(scratchmu)*eps(objold)
22: λ=5.481834282156947e-5, pct_dev=0.03247927557229435
23: λ=4.994843233098504e-5, pct_dev=0.03273569741126037
24: λ=4.5511151266348316e-5, pct_dev=0.03295587690875246
step-halving because obj=0.004752931599085589 > 0.00475293159876313 + 5.348152476436496e-15 = length(scratchmu)*eps(objold)
25: λ=4.1468066021834846e-5, pct_dev=0.033144545621176746
step-halving because obj=0.004749571406770409 > 0.004749571406369983 + 5.348152476436496e-15 = length(scratchmu)*eps(objold)
26: λ=3.778415732723409e-5, pct_dev=0.03330588958302205
27: λ=3.442751692778391e-5, pct_dev=0.033443599554707104
28: λ=3.136907121013224e-5, pct_dev=0.03356091938831385
29: λ=2.8582329380607118e-5, pct_dev=0.03366069162108365
30: λ=2.6043154014634736e-5, pct_dev=0.03374539711868052
31: λ=2.372955198991474e-5, pct_dev=0.033817196120928816
32: λ=2.1621483992516497e-5, pct_dev=0.033877963105122144
33: λ=1.9700690945928288e-5, pct_dev=0.03392931958095369
34: λ=1.795053585967147e-5, pct_dev=0.033972664521059515
35: λ=1.6355859727648175e-5, pct_dev=0.0340092017437984
36: λ=1.4902850228082263e-5, pct_dev=0.03403996415048871
37: λ=1.3578922087795775e-5, pct_dev=0.03406583601656832
38: λ=1.2372608074593485e-5, pct_dev=0.034087572372232255
step-halving because obj=0.0047230553668729195 > 0.004723055366334534 + 5.348152476436496e-15 = length(scratchmu)*eps(objold)
39: λ=1.1273459673583369e-5, pct_dev=0.034105816996643945
step-halving because obj=0.004721965550004314 > 0.004721965549936855 + 5.348152476436496e-15 = length(scratchmu)*eps(objold)
40: λ=1.0271956587139042e-5, pct_dev=0.0341211173866095
41: λ=9.359424274636258e-6, pct_dev=0.0341339379041421
42: λ=8.527958817731798e-6, pct_dev=0.03414467235331431
step-halving because obj=0.004719213180408082 > 0.0047192131803512295 + 5.348152476436496e-15 = length(scratchmu)*eps(objold)
Iteration: 1, deviance: 204.0380396102879, diff.dev.:284.0542927421118
Iteration: 2, deviance: 103.01893015575959, diff.dev.:101.01910945452832
Iteration: 3, deviance: 69.83490468963156, diff.dev.:33.184025466128034
Iteration: 4, deviance: 60.607472505222646, diff.dev.:9.227432184408912
Iteration: 5, deviance: 58.58206318973799, diff.dev.:2.0254093154846586
Iteration: 6, deviance: 58.153700985860056, diff.dev.:0.42836220387793134
Iteration: 7, deviance: 58.09051069340532, diff.dev.:0.06319029245473473
Iteration: 8, deviance: 58.08834852763462, diff.dev.:0.0021621657706987207
Iteration: 9, deviance: 58.088345222699864, diff.dev.:3.3049347578639754e-6
1: λ=0.00038674044876033174, pct_dev=5.408929673822449e-6
2: λ=0.00035238349319380514, pct_dev=0.004046376329978285
3: λ=0.0003210787148680711, pct_dev=0.007611478289555773
4: λ=0.0002925549667692108, pct_dev=0.010760649203050532
5: λ=0.0002665651898367098, pct_dev=0.013544519504385955
6: λ=0.00024288427305606497, pct_dev=0.016006274304332435
7: λ=0.0002213071036548711, pct_dev=0.01818307250563489
8: λ=0.00020164679051410886, pct_dev=0.02010714327092178
9: λ=0.000183733045406678, pct_dev=0.02180664182504133
10: λ=0.000167410708042241, pct_dev=0.023306323185635414
11: λ=0.00015253840214301398, pct_dev=0.024628076465672666
12: λ=0.0001389873109100814, pct_dev=0.02579135132999444
13: λ=0.0001266400612739101, pct_dev=0.026813500399619716
14: λ=0.0001153897072649705, pct_dev=0.027710055819832546
15: λ=0.00010513880369890995, pct_dev=0.028494954136865425
16: λ=9.579856215298414e-5, pct_dev=0.029180720603098842
17: λ=8.728808192321398e-5, pct_dev=0.0297786217165672
18: λ=7.953364930119035e-5, pct_dev=0.030298793003017743
19: λ=7.246809910119532e-5, pct_dev=0.030750347604051487
20: λ=6.60302329074955e-5, pct_dev=0.031141470061326393
21: λ=6.016428900294135e-5, pct_dev=0.0314794987187319
22: λ=5.481945938764883e-5, pct_dev=0.031770999359783225
23: λ=4.994944970441121e-5, pct_dev=0.03202183203722353
24: λ=4.5512078259123385e-5, pct_dev=0.032237212510321744
25: λ=4.146891066312668e-5, pct_dev=0.03242176927755969
26: λ=3.778492693292148e-5, pct_dev=0.03257959685858758
27: λ=3.442821816382316e-5, pct_dev=0.03271430573274792
28: λ=3.136971015029444e-5, pct_dev=0.032829068905250725
29: λ=2.8582911559086306e-5, pct_dev=0.03292666687394974
30: λ=2.604368447398234e-5, pct_dev=0.033009526681117785
31: λ=2.3730035324715953e-5, pct_dev=0.03307976125064971
32: λ=2.1621924389186096e-5, pct_dev=0.03313920409341786
33: λ=1.9701092218971507e-5, pct_dev=0.033189441530157016
34: λ=1.7950901484723522e-5, pct_dev=0.03323184210402219
35: λ=1.63561928715783e-5, pct_dev=0.033267583266010314
36: λ=1.4903153776423796e-5, pct_dev=0.03329767543883244
37: λ=1.3579198669739283e-5, pct_dev=0.03332298359031394
38: λ=1.2372860085759425e-5, pct_dev=0.03334424646583123
39: λ=1.127368929677188e-5, pct_dev=0.0333620936411545
40: λ=1.027216581123637e-5, pct_dev=0.033377060566930905
41: λ=9.359614911841426e-6, pct_dev=0.033389601777973676
42: λ=8.528132519253062e-6, pct_dev=0.03340010243927127
Iteration: 1, deviance: 202.88392988622178, diff.dev.:283.33062895363446
Iteration: 2, deviance: 103.34453979599363, diff.dev.:99.53939009022815
Iteration: 3, deviance: 70.8605677714221, diff.dev.:32.48397202457153
Iteration: 4, deviance: 61.88239574380505, diff.dev.:8.978172027617049
Iteration: 5, deviance: 59.91832501231309, diff.dev.:1.964070731491958
Iteration: 6, deviance: 59.501911842558584, diff.dev.:0.41641316975450593
Iteration: 7, deviance: 59.441417118304834, diff.dev.:0.060494724253750576
Iteration: 8, deviance: 59.43942365499241, diff.dev.:0.001993463312423671
Iteration: 9, deviance: 59.4394208386435, diff.dev.:2.816348910528177e-6
[ Info: Testing dmr degenerate cases. The 2 following warnings by workers are expected ...
┌ Warning: fitgl! failed on count dimension 2 with frequencies OrderedCollections.OrderedDict(0.0 => 200) and will return zero coefs (ErrorException("IRLS failed to converge in 30 iterations at λ = 4.3709033880452197e-7"))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/dmr.jl:412
┌ Warning: fitgl failed for countsj with frequencies OrderedCollections.OrderedDict(0.0 => 200) and will return missing path (ErrorException("IRLS failed to converge in 30 iterations at λ = 4.3709033880452197e-7"))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/dmr.jl:375
[ Info: Testing hdmr degenerate cases. The 2 following warnings by workers are expected ...
┌ Warning: hurdle_regression! failed on count dimension 2 with frequencies OrderedCollections.OrderedDict(0.0 => 200) and will return zero coefs (ErrorException("y is all zeros! There is nothing to explain."))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/hdmr.jl:456
┌ Warning: fit(InclusionRepetition...) failed for countsj with frequencies OrderedCollections.OrderedDict(0.0 => 200) and will return missing path (ErrorException("y is all zeros! There is nothing to explain."))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/hdmr.jl:332
[ Info: Testing hdmr degenerate cases. The 12 following warnings by workers are expected ...
┌ Warning: hurdle_regression! failed on count dimension 3 with frequencies OrderedCollections.OrderedDict(1.0 => 65,2.0 => 52,3.0 => 21,4.0 => 9,5.0 => 12,6.0 => 5,7.0 => 8,8.0 => 9,9.0 => 9,10.0 => 10) and will return zero coefs (LinearAlgebra.PosDefException(1))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/hdmr.jl:456
┌ Warning: hurdle_regression! failed on count dimension 2 with frequencies OrderedCollections.OrderedDict(1.0 => 44,2.0 => 29,3.0 => 20,4.0 => 12,5.0 => 13,6.0 => 16,7.0 => 20,8.0 => 14,9.0 => 14,10.0 => 18) and will return zero coefs (LinearAlgebra.PosDefException(1))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/hdmr.jl:456
┌ Warning: hurdle_regression! failed on count dimension 1 with frequencies OrderedCollections.OrderedDict(1.0 => 35,2.0 => 19,3.0 => 21,4.0 => 17,5.0 => 17,6.0 => 20,7.0 => 21,8.0 => 10,9.0 => 14,10.0 => 26) and will return zero coefs (LinearAlgebra.PosDefException(1))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/hdmr.jl:456
┌ Warning: hurdle_regression! failed on count dimension 4 with frequencies OrderedCollections.OrderedDict(1.0 => 13,2.0 => 16,3.0 => 35,4.0 => 38,5.0 => 36,6.0 => 29,7.0 => 16,8.0 => 12,9.0 => 5) and will return zero coefs (LinearAlgebra.PosDefException(1))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/hdmr.jl:456
┌ Warning: fit(InclusionRepetition...) failed for countsj with frequencies OrderedCollections.OrderedDict(1.0 => 13,2.0 => 16,3.0 => 35,4.0 => 38,5.0 => 36,6.0 => 29,7.0 => 16,8.0 => 12,9.0 => 5) and will return missing path (LinearAlgebra.PosDefException(1))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/hdmr.jl:332
┌ Warning: fit(InclusionRepetition...) failed for countsj with frequencies OrderedCollections.OrderedDict(1.0 => 65,2.0 => 52,3.0 => 21,4.0 => 9,5.0 => 12,6.0 => 5,7.0 => 8,8.0 => 9,9.0 => 9,10.0 => 10) and will return missing path (LinearAlgebra.PosDefException(1))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/hdmr.jl:332
┌ Warning: fit(InclusionRepetition...) failed for countsj with frequencies OrderedCollections.OrderedDict(1.0 => 35,2.0 => 19,3.0 => 21,4.0 => 17,5.0 => 17,6.0 => 20,7.0 => 21,8.0 => 10,9.0 => 14,10.0 => 26) and will return missing path (LinearAlgebra.PosDefException(1))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/hdmr.jl:332
┌ Warning: fit(InclusionRepetition...) failed for countsj with frequencies OrderedCollections.OrderedDict(1.0 => 44,2.0 => 29,3.0 => 20,4.0 => 12,5.0 => 13,6.0 => 16,7.0 => 20,8.0 => 14,9.0 => 14,10.0 => 18) and will return missing path (LinearAlgebra.PosDefException(1))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/hdmr.jl:332
┌ Warning: fit(InclusionRepetition...) failed for countsj with frequencies OrderedCollections.OrderedDict(1.0 => 35,2.0 => 19,3.0 => 21,4.0 => 17,5.0 => 17,6.0 => 20,7.0 => 21,8.0 => 10,9.0 => 14,10.0 => 26) and will return missing path (LinearAlgebra.PosDefException(1))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/hdmr.jl:332
┌ Warning: fit(InclusionRepetition...) failed for countsj with frequencies OrderedCollections.OrderedDict(1.0 => 44,2.0 => 29,3.0 => 20,4.0 => 12,5.0 => 13,6.0 => 16,7.0 => 20,8.0 => 14,9.0 => 14,10.0 => 18) and will return missing path (LinearAlgebra.PosDefException(1))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/hdmr.jl:332
┌ Warning: fit(InclusionRepetition...) failed for countsj with frequencies OrderedCollections.OrderedDict(1.0 => 65,2.0 => 52,3.0 => 21,4.0 => 9,5.0 => 12,6.0 => 5,7.0 => 8,8.0 => 9,9.0 => 9,10.0 => 10) and will return missing path (LinearAlgebra.PosDefException(1))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/hdmr.jl:332
┌ Warning: fit(InclusionRepetition...) failed for countsj with frequencies OrderedCollections.OrderedDict(1.0 => 13,2.0 => 16,3.0 => 35,4.0 => 38,5.0 => 36,6.0 => 29,7.0 => 16,8.0 => 12,9.0 => 5) and will return missing path (LinearAlgebra.PosDefException(1))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/hdmr.jl:332
[ Info: Testing hdmr degenerate cases. The 2 following warnings by workers are expected ...
┌ Warning: hurdle_regression! failed on count dimension 2 with frequencies OrderedCollections.OrderedDict(0.0 => 200) and will return zero coefs (ErrorException("y is all zeros! There is nothing to explain."))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/hdmr.jl:456
┌ Warning: fit(Hurdle...) failed for countsj with frequencies OrderedCollections.OrderedDict(0.0 => 200) and will return missing path (ErrorException("y is all zeros! There is nothing to explain."))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/hdmr.jl:332
Test Summary: | Pass Total
HurdleDMR | 1303 1303
Testing HurdleDMR tests passed
Results with Julia v1.3.0
Testing was successful .
Last evaluation was ago and took 11 minutes, 43 seconds.
Click here to download the log file.
Click here to show the log contents.
Resolving package versions...
Installed SortingAlgorithms ─────────── v0.3.1
Installed URIParser ─────────────────── v0.4.0
Installed LambertW ──────────────────── v0.4.3
Installed Arpack ────────────────────── v0.3.1
Installed FFTW ──────────────────────── v1.1.0
Installed QuadGK ────────────────────── v2.1.1
Installed DataStructures ────────────── v0.17.6
Installed HurdleDMR ─────────────────── v1.3.0
Installed BinaryProvider ────────────── v0.5.8
Installed Compat ────────────────────── v2.2.0
Installed Parsers ───────────────────── v0.3.10
Installed Missings ──────────────────── v0.4.3
Installed IterTools ─────────────────── v1.3.0
Installed StatsFuns ─────────────────── v0.9.0
Installed LoggingExtras ─────────────── v0.3.0
Installed Distributions ─────────────── v0.21.9
Installed Rmath ─────────────────────── v0.5.1
Installed JSON ──────────────────────── v0.21.0
Installed TableTraits ───────────────── v1.0.0
Installed SpecialFunctions ──────────── v0.8.0
Installed DSP ───────────────────────── v0.6.2
Installed OrderedCollections ────────── v1.1.0
Installed BinDeps ───────────────────── v0.8.10
Installed RecipesBase ───────────────── v0.7.0
Installed DataAPI ───────────────────── v1.1.0
Installed ShiftedArrays ─────────────── v1.0.0
Installed Lasso ─────────────────────── v0.5.0
Installed DataValueInterfaces ───────── v1.0.0
Installed Tables ────────────────────── v0.2.11
Installed Polynomials ───────────────── v0.6.0
Installed StatsModels ───────────────── v0.6.7
Installed MLBase ────────────────────── v0.8.0
Installed GLM ───────────────────────── v1.3.4
Installed Conda ─────────────────────── v1.3.0
Installed VersionParsing ────────────── v1.1.3
Installed Reexport ──────────────────── v0.2.0
Installed IteratorInterfaceExtensions ─ v1.0.0
Installed PDMats ────────────────────── v0.9.10
Installed StatsBase ─────────────────── v0.32.0
Installed AbstractFFTs ──────────────── v0.5.0
Updating `~/.julia/environments/v1.3/Project.toml`
[f9e53bcf] + HurdleDMR v1.3.0
Updating `~/.julia/environments/v1.3/Manifest.toml`
[621f4979] + AbstractFFTs v0.5.0
[7d9fca2a] + Arpack v0.3.1
[9e28174c] + BinDeps v0.8.10
[b99e7846] + BinaryProvider v0.5.8
[34da2185] + Compat v2.2.0
[8f4d0f93] + Conda v1.3.0
[717857b8] + DSP v0.6.2
[9a962f9c] + DataAPI v1.1.0
[864edb3b] + DataStructures v0.17.6
[e2d170a0] + DataValueInterfaces v1.0.0
[31c24e10] + Distributions v0.21.9
[7a1cc6ca] + FFTW v1.1.0
[38e38edf] + GLM v1.3.4
[f9e53bcf] + HurdleDMR v1.3.0
[c8e1da08] + IterTools v1.3.0
[82899510] + IteratorInterfaceExtensions v1.0.0
[682c06a0] + JSON v0.21.0
[984bce1d] + LambertW v0.4.3
[b4fcebef] + Lasso v0.5.0
[e6f89c97] + LoggingExtras v0.3.0
[f0e99cf1] + MLBase v0.8.0
[e1d29d7a] + Missings v0.4.3
[bac558e1] + OrderedCollections v1.1.0
[90014a1f] + PDMats v0.9.10
[69de0a69] + Parsers v0.3.10
[f27b6e38] + Polynomials v0.6.0
[1fd47b50] + QuadGK v2.1.1
[3cdcf5f2] + RecipesBase v0.7.0
[189a3867] + Reexport v0.2.0
[79098fc4] + Rmath v0.5.1
[1277b4bf] + ShiftedArrays v1.0.0
[a2af1166] + SortingAlgorithms v0.3.1
[276daf66] + SpecialFunctions v0.8.0
[2913bbd2] + StatsBase v0.32.0
[4c63d2b9] + StatsFuns v0.9.0
[3eaba693] + StatsModels v0.6.7
[3783bdb8] + TableTraits v1.0.0
[bd369af6] + Tables v0.2.11
[30578b45] + URIParser v0.4.0
[81def892] + VersionParsing v1.1.3
[2a0f44e3] + Base64
[ade2ca70] + Dates
[8bb1440f] + DelimitedFiles
[8ba89e20] + Distributed
[b77e0a4c] + InteractiveUtils
[76f85450] + LibGit2
[8f399da3] + Libdl
[37e2e46d] + LinearAlgebra
[56ddb016] + Logging
[d6f4376e] + Markdown
[a63ad114] + Mmap
[44cfe95a] + Pkg
[de0858da] + Printf
[3fa0cd96] + REPL
[9a3f8284] + Random
[ea8e919c] + SHA
[9e88b42a] + Serialization
[1a1011a3] + SharedArrays
[6462fe0b] + Sockets
[2f01184e] + SparseArrays
[10745b16] + Statistics
[4607b0f0] + SuiteSparse
[8dfed614] + Test
[cf7118a7] + UUIDs
[4ec0a83e] + Unicode
Building Arpack ──────────→ `~/.julia/packages/Arpack/cu5By/deps/build.log`
Building Conda ───────────→ `~/.julia/packages/Conda/kLXeC/deps/build.log`
Building FFTW ────────────→ `~/.julia/packages/FFTW/loJ3F/deps/build.log`
Building Rmath ───────────→ `~/.julia/packages/Rmath/4wt82/deps/build.log`
Building SpecialFunctions → `~/.julia/packages/SpecialFunctions/ne2iw/deps/build.log`
Testing HurdleDMR
Resolving package versions...
Installed StaticArrays ────── v0.12.1
Installed LazyArrays ──────── v0.14.10
Installed MacroTools ──────── v0.5.2
Installed ArrayLayouts ────── v0.1.5
Installed DataFrames ──────── v0.19.4
Installed CategoricalArrays ─ v0.7.3
Installed InvertedIndices ─── v1.0.0
Installed PooledArrays ────── v0.5.2
Installed FilePathsBase ───── v0.7.0
Installed FillArrays ──────── v0.8.2
Installed WeakRefStrings ──── v0.6.1
Installed CSV ─────────────── v0.5.18
Status `/tmp/jl_F3i9tX/Manifest.toml`
[621f4979] AbstractFFTs v0.5.0
[7d9fca2a] Arpack v0.3.1
[4c555306] ArrayLayouts v0.1.5
[9e28174c] BinDeps v0.8.10
[b99e7846] BinaryProvider v0.5.8
[336ed68f] CSV v0.5.18
[324d7699] CategoricalArrays v0.7.3
[34da2185] Compat v2.2.0
[8f4d0f93] Conda v1.3.0
[717857b8] DSP v0.6.2
[9a962f9c] DataAPI v1.1.0
[a93c6f00] DataFrames v0.19.4
[864edb3b] DataStructures v0.17.6
[e2d170a0] DataValueInterfaces v1.0.0
[31c24e10] Distributions v0.21.9
[7a1cc6ca] FFTW v1.1.0
[48062228] FilePathsBase v0.7.0
[1a297f60] FillArrays v0.8.2
[38e38edf] GLM v1.3.4
[f9e53bcf] HurdleDMR v1.3.0
[41ab1584] InvertedIndices v1.0.0
[c8e1da08] IterTools v1.3.0
[82899510] IteratorInterfaceExtensions v1.0.0
[682c06a0] JSON v0.21.0
[984bce1d] LambertW v0.4.3
[b4fcebef] Lasso v0.5.0
[5078a376] LazyArrays v0.14.10
[e6f89c97] LoggingExtras v0.3.0
[f0e99cf1] MLBase v0.8.0
[1914dd2f] MacroTools v0.5.2
[e1d29d7a] Missings v0.4.3
[bac558e1] OrderedCollections v1.1.0
[90014a1f] PDMats v0.9.10
[69de0a69] Parsers v0.3.10
[f27b6e38] Polynomials v0.6.0
[2dfb63ee] PooledArrays v0.5.2
[1fd47b50] QuadGK v2.1.1
[3cdcf5f2] RecipesBase v0.7.0
[189a3867] Reexport v0.2.0
[79098fc4] Rmath v0.5.1
[1277b4bf] ShiftedArrays v1.0.0
[a2af1166] SortingAlgorithms v0.3.1
[276daf66] SpecialFunctions v0.8.0
[90137ffa] StaticArrays v0.12.1
[2913bbd2] StatsBase v0.32.0
[4c63d2b9] StatsFuns v0.9.0
[3eaba693] StatsModels v0.6.7
[3783bdb8] TableTraits v1.0.0
[bd369af6] Tables v0.2.11
[30578b45] URIParser v0.4.0
[81def892] VersionParsing v1.1.3
[ea10d353] WeakRefStrings v0.6.1
[2a0f44e3] Base64 [`@stdlib/Base64`]
[ade2ca70] Dates [`@stdlib/Dates`]
[8bb1440f] DelimitedFiles [`@stdlib/DelimitedFiles`]
[8ba89e20] Distributed [`@stdlib/Distributed`]
[9fa8497b] Future [`@stdlib/Future`]
[b77e0a4c] InteractiveUtils [`@stdlib/InteractiveUtils`]
[76f85450] LibGit2 [`@stdlib/LibGit2`]
[8f399da3] Libdl [`@stdlib/Libdl`]
[37e2e46d] LinearAlgebra [`@stdlib/LinearAlgebra`]
[56ddb016] Logging [`@stdlib/Logging`]
[d6f4376e] Markdown [`@stdlib/Markdown`]
[a63ad114] Mmap [`@stdlib/Mmap`]
[44cfe95a] Pkg [`@stdlib/Pkg`]
[de0858da] Printf [`@stdlib/Printf`]
[3fa0cd96] REPL [`@stdlib/REPL`]
[9a3f8284] Random [`@stdlib/Random`]
[ea8e919c] SHA [`@stdlib/SHA`]
[9e88b42a] Serialization [`@stdlib/Serialization`]
[1a1011a3] SharedArrays [`@stdlib/SharedArrays`]
[6462fe0b] Sockets [`@stdlib/Sockets`]
[2f01184e] SparseArrays [`@stdlib/SparseArrays`]
[10745b16] Statistics [`@stdlib/Statistics`]
[4607b0f0] SuiteSparse [`@stdlib/SuiteSparse`]
[8dfed614] Test [`@stdlib/Test`]
[cf7118a7] UUIDs [`@stdlib/UUIDs`]
[4ec0a83e] Unicode [`@stdlib/Unicode`]
[ Info: Starting 4 parallel workers for tests...
[ Info: 4 parallel workers started
[ Info: Testing hurdle degenerate cases. The following warnings about step-halving are expected ...
1: λ=0.000386732571607375, pct_dev=6.491976604627858e-6
2: λ=0.00035237631582540674, pct_dev=0.004137275679515495
step-halving because obj=0.004873710484493199 > 0.0048737104844521545 + 5.348152476436496e-15 = length(scratchmu)*eps(objold)
3: λ=0.0003210721751172995, pct_dev=0.007781659027663257
4: λ=0.00029254900799187346, pct_dev=0.011000893812644796
5: λ=0.00026655976042072805, pct_dev=0.01384672457319358
6: λ=0.00024287932597443493, pct_dev=0.01636328834963452
step-halving because obj=0.004853629958394753 > 0.00485362995832963 + 5.348152476436496e-15 = length(scratchmu)*eps(objold)
7: λ=0.00022130259605833834, pct_dev=0.018588564316925682
step-halving because obj=0.004847225402105616 > 0.004847225402075316 + 5.348152476436496e-15 = length(scratchmu)*eps(objold)
8: λ=0.00020164268336002862, pct_dev=0.020555493976648687
step-halving because obj=0.004840589108480022 > 0.004840589108449965 + 5.348152476436496e-15 = length(scratchmu)*eps(objold)
9: λ=0.00018372930312084647, pct_dev=0.022292855685093316
10: λ=0.00016740729821076853, pct_dev=0.023825953055227722
11: λ=0.00015253529523157167, pct_dev=0.02517716069551157
12: λ=0.0001389844800080886, pct_dev=0.026366360317267468
13: λ=0.00012663748186144804, pct_dev=0.027411290020289636
14: λ=0.00011538735700040242, pct_dev=0.02832782749366669
15: λ=0.00010513666222536851, pct_dev=0.029130219588688777
step-halving because obj=0.0047950177502431605 > 0.004795017750074621 + 5.348152476436496e-15 = length(scratchmu)*eps(objold)
16: λ=9.579661092204997e-5, pct_dev=0.029831270237958174
step-halving because obj=0.004789253164598393 > 0.004789253164442045 + 5.348152476436496e-15 = length(scratchmu)*eps(objold)
17: λ=8.728630403425833e-5, pct_dev=0.030442496928184237
step-halving because obj=0.004783753703245748 > 0.004783753703178281 + 5.348152476436496e-15 = length(scratchmu)*eps(objold)
18: λ=7.953202935498933e-5, pct_dev=0.030974261196463515
19: λ=7.246662306655003e-5, pct_dev=0.031435879206021755
20: λ=6.60288879997001e-5, pct_dev=0.03183571788072681
21: λ=6.016306357304766e-5, pct_dev=0.03218127930818637
step-halving because obj=0.004764518539996998 > 0.004764518539672642 + 5.348152476436496e-15 = length(scratchmu)*eps(objold)
22: λ=5.481834282156947e-5, pct_dev=0.03247927557229435
23: λ=4.994843233098504e-5, pct_dev=0.03273569741126037
24: λ=4.5511151266348316e-5, pct_dev=0.03295587690875246
step-halving because obj=0.004752931599085589 > 0.00475293159876313 + 5.348152476436496e-15 = length(scratchmu)*eps(objold)
25: λ=4.1468066021834846e-5, pct_dev=0.033144545621176746
step-halving because obj=0.004749571406770409 > 0.004749571406369983 + 5.348152476436496e-15 = length(scratchmu)*eps(objold)
26: λ=3.778415732723409e-5, pct_dev=0.03330588958302205
27: λ=3.442751692778391e-5, pct_dev=0.033443599554707104
28: λ=3.136907121013224e-5, pct_dev=0.03356091938831385
29: λ=2.8582329380607118e-5, pct_dev=0.03366069162108365
30: λ=2.6043154014634736e-5, pct_dev=0.03374539711868052
31: λ=2.372955198991474e-5, pct_dev=0.033817196120928816
32: λ=2.1621483992516497e-5, pct_dev=0.033877963105122144
33: λ=1.9700690945928288e-5, pct_dev=0.03392931958095369
34: λ=1.795053585967147e-5, pct_dev=0.033972664521059515
35: λ=1.6355859727648175e-5, pct_dev=0.0340092017437984
36: λ=1.4902850228082263e-5, pct_dev=0.03403996415048871
37: λ=1.3578922087795775e-5, pct_dev=0.03406583601656832
38: λ=1.2372608074593485e-5, pct_dev=0.034087572372232255
step-halving because obj=0.0047230553668729195 > 0.004723055366334534 + 5.348152476436496e-15 = length(scratchmu)*eps(objold)
39: λ=1.1273459673583369e-5, pct_dev=0.034105816996643945
step-halving because obj=0.004721965550004314 > 0.004721965549936855 + 5.348152476436496e-15 = length(scratchmu)*eps(objold)
40: λ=1.0271956587139042e-5, pct_dev=0.0341211173866095
41: λ=9.359424274636258e-6, pct_dev=0.0341339379041421
42: λ=8.527958817731798e-6, pct_dev=0.03414467235331431
step-halving because obj=0.004719213180408082 > 0.0047192131803512295 + 5.348152476436496e-15 = length(scratchmu)*eps(objold)
Iteration: 1, deviance: 204.0380396102879, diff.dev.:284.0542927421118
Iteration: 2, deviance: 103.01893015575959, diff.dev.:101.01910945452832
Iteration: 3, deviance: 69.83490468963156, diff.dev.:33.184025466128034
Iteration: 4, deviance: 60.607472505222646, diff.dev.:9.227432184408912
Iteration: 5, deviance: 58.58206318973799, diff.dev.:2.0254093154846586
Iteration: 6, deviance: 58.153700985860056, diff.dev.:0.42836220387793134
Iteration: 7, deviance: 58.09051069340532, diff.dev.:0.06319029245473473
Iteration: 8, deviance: 58.08834852763462, diff.dev.:0.0021621657706987207
Iteration: 9, deviance: 58.088345222699864, diff.dev.:3.3049347578639754e-6
1: λ=0.00038674044876033174, pct_dev=5.408929673822449e-6
2: λ=0.00035238349319380514, pct_dev=0.004046376329978285
3: λ=0.0003210787148680711, pct_dev=0.007611478289555773
4: λ=0.0002925549667692108, pct_dev=0.010760649203050532
5: λ=0.0002665651898367098, pct_dev=0.013544519504385955
6: λ=0.00024288427305606497, pct_dev=0.016006274304332435
7: λ=0.0002213071036548711, pct_dev=0.01818307250563489
8: λ=0.00020164679051410886, pct_dev=0.02010714327092178
9: λ=0.000183733045406678, pct_dev=0.02180664182504133
10: λ=0.000167410708042241, pct_dev=0.023306323185635414
11: λ=0.00015253840214301398, pct_dev=0.024628076465672666
12: λ=0.0001389873109100814, pct_dev=0.02579135132999444
13: λ=0.0001266400612739101, pct_dev=0.026813500399619716
14: λ=0.0001153897072649705, pct_dev=0.027710055819832546
15: λ=0.00010513880369890995, pct_dev=0.028494954136865425
16: λ=9.579856215298414e-5, pct_dev=0.029180720603098842
17: λ=8.728808192321398e-5, pct_dev=0.0297786217165672
18: λ=7.953364930119035e-5, pct_dev=0.030298793003017743
19: λ=7.246809910119532e-5, pct_dev=0.030750347604051487
20: λ=6.60302329074955e-5, pct_dev=0.031141470061326393
21: λ=6.016428900294135e-5, pct_dev=0.0314794987187319
22: λ=5.481945938764883e-5, pct_dev=0.031770999359783225
23: λ=4.994944970441121e-5, pct_dev=0.03202183203722353
24: λ=4.5512078259123385e-5, pct_dev=0.032237212510321744
25: λ=4.146891066312668e-5, pct_dev=0.03242176927755969
26: λ=3.778492693292148e-5, pct_dev=0.03257959685858758
27: λ=3.442821816382316e-5, pct_dev=0.03271430573274792
28: λ=3.136971015029444e-5, pct_dev=0.032829068905250725
29: λ=2.8582911559086306e-5, pct_dev=0.03292666687394974
30: λ=2.604368447398234e-5, pct_dev=0.033009526681117785
31: λ=2.3730035324715953e-5, pct_dev=0.03307976125064971
32: λ=2.1621924389186096e-5, pct_dev=0.03313920409341786
33: λ=1.9701092218971507e-5, pct_dev=0.033189441530157016
34: λ=1.7950901484723522e-5, pct_dev=0.03323184210402219
35: λ=1.63561928715783e-5, pct_dev=0.033267583266010314
36: λ=1.4903153776423796e-5, pct_dev=0.03329767543883244
37: λ=1.3579198669739283e-5, pct_dev=0.03332298359031394
38: λ=1.2372860085759425e-5, pct_dev=0.03334424646583123
39: λ=1.127368929677188e-5, pct_dev=0.0333620936411545
40: λ=1.027216581123637e-5, pct_dev=0.033377060566930905
41: λ=9.359614911841426e-6, pct_dev=0.033389601777973676
42: λ=8.528132519253062e-6, pct_dev=0.03340010243927127
Iteration: 1, deviance: 202.88392988622178, diff.dev.:283.33062895363446
Iteration: 2, deviance: 103.34453979599363, diff.dev.:99.53939009022815
Iteration: 3, deviance: 70.8605677714221, diff.dev.:32.48397202457153
Iteration: 4, deviance: 61.88239574380505, diff.dev.:8.978172027617049
Iteration: 5, deviance: 59.91832501231309, diff.dev.:1.964070731491958
Iteration: 6, deviance: 59.501911842558584, diff.dev.:0.41641316975450593
Iteration: 7, deviance: 59.441417118304834, diff.dev.:0.060494724253750576
Iteration: 8, deviance: 59.43942365499241, diff.dev.:0.001993463312423671
Iteration: 9, deviance: 59.4394208386435, diff.dev.:2.816348910528177e-6
[ Info: Testing dmr degenerate cases. The 2 following warnings by workers are expected ...
┌ Warning: fitgl! failed on count dimension 2 with frequencies OrderedCollections.OrderedDict(0.0 => 200) and will return zero coefs (ErrorException("IRLS failed to converge in 30 iterations at λ = 4.3709033880452197e-7"))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/dmr.jl:412
┌ Warning: fitgl failed for countsj with frequencies OrderedCollections.OrderedDict(0.0 => 200) and will return missing path (ErrorException("IRLS failed to converge in 30 iterations at λ = 4.3709033880452197e-7"))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/dmr.jl:375
[ Info: Testing hdmr degenerate cases. The 2 following warnings by workers are expected ...
┌ Warning: hurdle_regression! failed on count dimension 2 with frequencies OrderedCollections.OrderedDict(0.0 => 200) and will return zero coefs (ErrorException("y is all zeros! There is nothing to explain."))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/hdmr.jl:456
┌ Warning: fit(InclusionRepetition...) failed for countsj with frequencies OrderedCollections.OrderedDict(0.0 => 200) and will return missing path (ErrorException("y is all zeros! There is nothing to explain."))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/hdmr.jl:332
[ Info: Testing hdmr degenerate cases. The 12 following warnings by workers are expected ...
┌ Warning: hurdle_regression! failed on count dimension 3 with frequencies OrderedCollections.OrderedDict(1.0 => 65,2.0 => 52,3.0 => 21,4.0 => 9,5.0 => 12,6.0 => 5,7.0 => 8,8.0 => 9,9.0 => 9,10.0 => 10) and will return zero coefs (LinearAlgebra.PosDefException(1))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/hdmr.jl:456
┌ Warning: hurdle_regression! failed on count dimension 1 with frequencies OrderedCollections.OrderedDict(1.0 => 35,2.0 => 19,3.0 => 21,4.0 => 17,5.0 => 17,6.0 => 20,7.0 => 21,8.0 => 10,9.0 => 14,10.0 => 26) and will return zero coefs (LinearAlgebra.PosDefException(1))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/hdmr.jl:456
┌ Warning: hurdle_regression! failed on count dimension 2 with frequencies OrderedCollections.OrderedDict(1.0 => 44,2.0 => 29,3.0 => 20,4.0 => 12,5.0 => 13,6.0 => 16,7.0 => 20,8.0 => 14,9.0 => 14,10.0 => 18) and will return zero coefs (LinearAlgebra.PosDefException(1))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/hdmr.jl:456
┌ Warning: hurdle_regression! failed on count dimension 4 with frequencies OrderedCollections.OrderedDict(1.0 => 13,2.0 => 16,3.0 => 35,4.0 => 38,5.0 => 36,6.0 => 29,7.0 => 16,8.0 => 12,9.0 => 5) and will return zero coefs (LinearAlgebra.PosDefException(1))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/hdmr.jl:456
┌ Warning: fit(InclusionRepetition...) failed for countsj with frequencies OrderedCollections.OrderedDict(1.0 => 13,2.0 => 16,3.0 => 35,4.0 => 38,5.0 => 36,6.0 => 29,7.0 => 16,8.0 => 12,9.0 => 5) and will return missing path (LinearAlgebra.PosDefException(1))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/hdmr.jl:332
┌ Warning: fit(InclusionRepetition...) failed for countsj with frequencies OrderedCollections.OrderedDict(1.0 => 65,2.0 => 52,3.0 => 21,4.0 => 9,5.0 => 12,6.0 => 5,7.0 => 8,8.0 => 9,9.0 => 9,10.0 => 10) and will return missing path (LinearAlgebra.PosDefException(1))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/hdmr.jl:332
┌ Warning: fit(InclusionRepetition...) failed for countsj with frequencies OrderedCollections.OrderedDict(1.0 => 44,2.0 => 29,3.0 => 20,4.0 => 12,5.0 => 13,6.0 => 16,7.0 => 20,8.0 => 14,9.0 => 14,10.0 => 18) and will return missing path (LinearAlgebra.PosDefException(1))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/hdmr.jl:332
┌ Warning: fit(InclusionRepetition...) failed for countsj with frequencies OrderedCollections.OrderedDict(1.0 => 35,2.0 => 19,3.0 => 21,4.0 => 17,5.0 => 17,6.0 => 20,7.0 => 21,8.0 => 10,9.0 => 14,10.0 => 26) and will return missing path (LinearAlgebra.PosDefException(1))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/hdmr.jl:332
┌ Warning: fit(InclusionRepetition...) failed for countsj with frequencies OrderedCollections.OrderedDict(1.0 => 35,2.0 => 19,3.0 => 21,4.0 => 17,5.0 => 17,6.0 => 20,7.0 => 21,8.0 => 10,9.0 => 14,10.0 => 26) and will return missing path (LinearAlgebra.PosDefException(1))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/hdmr.jl:332
┌ Warning: fit(InclusionRepetition...) failed for countsj with frequencies OrderedCollections.OrderedDict(1.0 => 65,2.0 => 52,3.0 => 21,4.0 => 9,5.0 => 12,6.0 => 5,7.0 => 8,8.0 => 9,9.0 => 9,10.0 => 10) and will return missing path (LinearAlgebra.PosDefException(1))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/hdmr.jl:332
┌ Warning: fit(InclusionRepetition...) failed for countsj with frequencies OrderedCollections.OrderedDict(1.0 => 13,2.0 => 16,3.0 => 35,4.0 => 38,5.0 => 36,6.0 => 29,7.0 => 16,8.0 => 12,9.0 => 5) and will return missing path (LinearAlgebra.PosDefException(1))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/hdmr.jl:332
┌ Warning: fit(InclusionRepetition...) failed for countsj with frequencies OrderedCollections.OrderedDict(1.0 => 44,2.0 => 29,3.0 => 20,4.0 => 12,5.0 => 13,6.0 => 16,7.0 => 20,8.0 => 14,9.0 => 14,10.0 => 18) and will return missing path (LinearAlgebra.PosDefException(1))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/hdmr.jl:332
[ Info: Testing hdmr degenerate cases. The 2 following warnings by workers are expected ...
┌ Warning: hurdle_regression! failed on count dimension 2 with frequencies OrderedCollections.OrderedDict(0.0 => 200) and will return zero coefs (ErrorException("y is all zeros! There is nothing to explain."))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/hdmr.jl:456
┌ Warning: fit(Hurdle...) failed for countsj with frequencies OrderedCollections.OrderedDict(0.0 => 200) and will return missing path (ErrorException("y is all zeros! There is nothing to explain."))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/hdmr.jl:332
Test Summary: | Pass Total
HurdleDMR | 1303 1303
Testing HurdleDMR tests passed
Results with Julia v1.3.1-pre-7704df0a5a
Testing was successful .
Last evaluation was ago and took 11 minutes, 36 seconds.
Click here to download the log file.
Click here to show the log contents.
Resolving package versions...
Installed Tables ────────────────────── v0.2.11
Installed Conda ─────────────────────── v1.3.0
Installed StatsModels ───────────────── v0.6.7
Installed QuadGK ────────────────────── v2.1.1
Installed DataStructures ────────────── v0.17.6
Installed SpecialFunctions ──────────── v0.8.0
Installed MLBase ────────────────────── v0.8.0
Installed HurdleDMR ─────────────────── v1.3.0
Installed BinDeps ───────────────────── v0.8.10
Installed Polynomials ───────────────── v0.6.0
Installed Compat ────────────────────── v2.2.0
Installed Arpack ────────────────────── v0.3.1
Installed StatsBase ─────────────────── v0.32.0
Installed URIParser ─────────────────── v0.4.0
Installed FFTW ──────────────────────── v1.1.0
Installed IterTools ─────────────────── v1.3.0
Installed Missings ──────────────────── v0.4.3
Installed StatsFuns ─────────────────── v0.9.0
Installed Rmath ─────────────────────── v0.5.1
Installed ShiftedArrays ─────────────── v1.0.0
Installed GLM ───────────────────────── v1.3.4
Installed TableTraits ───────────────── v1.0.0
Installed LambertW ──────────────────── v0.4.3
Installed BinaryProvider ────────────── v0.5.8
Installed Lasso ─────────────────────── v0.5.0
Installed DataValueInterfaces ───────── v1.0.0
Installed AbstractFFTs ──────────────── v0.5.0
Installed RecipesBase ───────────────── v0.7.0
Installed IteratorInterfaceExtensions ─ v1.0.0
Installed Reexport ──────────────────── v0.2.0
Installed LoggingExtras ─────────────── v0.3.0
Installed DataAPI ───────────────────── v1.1.0
Installed JSON ──────────────────────── v0.21.0
Installed Distributions ─────────────── v0.21.9
Installed PDMats ────────────────────── v0.9.10
Installed Parsers ───────────────────── v0.3.10
Installed VersionParsing ────────────── v1.1.3
Installed OrderedCollections ────────── v1.1.0
Installed SortingAlgorithms ─────────── v0.3.1
Installed DSP ───────────────────────── v0.6.2
Updating `~/.julia/environments/v1.3/Project.toml`
[f9e53bcf] + HurdleDMR v1.3.0
Updating `~/.julia/environments/v1.3/Manifest.toml`
[621f4979] + AbstractFFTs v0.5.0
[7d9fca2a] + Arpack v0.3.1
[9e28174c] + BinDeps v0.8.10
[b99e7846] + BinaryProvider v0.5.8
[34da2185] + Compat v2.2.0
[8f4d0f93] + Conda v1.3.0
[717857b8] + DSP v0.6.2
[9a962f9c] + DataAPI v1.1.0
[864edb3b] + DataStructures v0.17.6
[e2d170a0] + DataValueInterfaces v1.0.0
[31c24e10] + Distributions v0.21.9
[7a1cc6ca] + FFTW v1.1.0
[38e38edf] + GLM v1.3.4
[f9e53bcf] + HurdleDMR v1.3.0
[c8e1da08] + IterTools v1.3.0
[82899510] + IteratorInterfaceExtensions v1.0.0
[682c06a0] + JSON v0.21.0
[984bce1d] + LambertW v0.4.3
[b4fcebef] + Lasso v0.5.0
[e6f89c97] + LoggingExtras v0.3.0
[f0e99cf1] + MLBase v0.8.0
[e1d29d7a] + Missings v0.4.3
[bac558e1] + OrderedCollections v1.1.0
[90014a1f] + PDMats v0.9.10
[69de0a69] + Parsers v0.3.10
[f27b6e38] + Polynomials v0.6.0
[1fd47b50] + QuadGK v2.1.1
[3cdcf5f2] + RecipesBase v0.7.0
[189a3867] + Reexport v0.2.0
[79098fc4] + Rmath v0.5.1
[1277b4bf] + ShiftedArrays v1.0.0
[a2af1166] + SortingAlgorithms v0.3.1
[276daf66] + SpecialFunctions v0.8.0
[2913bbd2] + StatsBase v0.32.0
[4c63d2b9] + StatsFuns v0.9.0
[3eaba693] + StatsModels v0.6.7
[3783bdb8] + TableTraits v1.0.0
[bd369af6] + Tables v0.2.11
[30578b45] + URIParser v0.4.0
[81def892] + VersionParsing v1.1.3
[2a0f44e3] + Base64
[ade2ca70] + Dates
[8bb1440f] + DelimitedFiles
[8ba89e20] + Distributed
[b77e0a4c] + InteractiveUtils
[76f85450] + LibGit2
[8f399da3] + Libdl
[37e2e46d] + LinearAlgebra
[56ddb016] + Logging
[d6f4376e] + Markdown
[a63ad114] + Mmap
[44cfe95a] + Pkg
[de0858da] + Printf
[3fa0cd96] + REPL
[9a3f8284] + Random
[ea8e919c] + SHA
[9e88b42a] + Serialization
[1a1011a3] + SharedArrays
[6462fe0b] + Sockets
[2f01184e] + SparseArrays
[10745b16] + Statistics
[4607b0f0] + SuiteSparse
[8dfed614] + Test
[cf7118a7] + UUIDs
[4ec0a83e] + Unicode
Building Conda ───────────→ `~/.julia/packages/Conda/kLXeC/deps/build.log`
Building SpecialFunctions → `~/.julia/packages/SpecialFunctions/ne2iw/deps/build.log`
Building Arpack ──────────→ `~/.julia/packages/Arpack/cu5By/deps/build.log`
Building FFTW ────────────→ `~/.julia/packages/FFTW/loJ3F/deps/build.log`
Building Rmath ───────────→ `~/.julia/packages/Rmath/4wt82/deps/build.log`
Testing HurdleDMR
Resolving package versions...
Installed WeakRefStrings ──── v0.6.1
Installed LazyArrays ──────── v0.14.10
Installed FillArrays ──────── v0.8.2
Installed DataFrames ──────── v0.19.4
Installed MacroTools ──────── v0.5.2
Installed ArrayLayouts ────── v0.1.5
Installed StaticArrays ────── v0.12.1
Installed FilePathsBase ───── v0.7.0
Installed PooledArrays ────── v0.5.2
Installed InvertedIndices ─── v1.0.0
Installed CategoricalArrays ─ v0.7.3
Installed CSV ─────────────── v0.5.18
Status `/tmp/jl_op4b53/Manifest.toml`
[621f4979] AbstractFFTs v0.5.0
[7d9fca2a] Arpack v0.3.1
[4c555306] ArrayLayouts v0.1.5
[9e28174c] BinDeps v0.8.10
[b99e7846] BinaryProvider v0.5.8
[336ed68f] CSV v0.5.18
[324d7699] CategoricalArrays v0.7.3
[34da2185] Compat v2.2.0
[8f4d0f93] Conda v1.3.0
[717857b8] DSP v0.6.2
[9a962f9c] DataAPI v1.1.0
[a93c6f00] DataFrames v0.19.4
[864edb3b] DataStructures v0.17.6
[e2d170a0] DataValueInterfaces v1.0.0
[31c24e10] Distributions v0.21.9
[7a1cc6ca] FFTW v1.1.0
[48062228] FilePathsBase v0.7.0
[1a297f60] FillArrays v0.8.2
[38e38edf] GLM v1.3.4
[f9e53bcf] HurdleDMR v1.3.0
[41ab1584] InvertedIndices v1.0.0
[c8e1da08] IterTools v1.3.0
[82899510] IteratorInterfaceExtensions v1.0.0
[682c06a0] JSON v0.21.0
[984bce1d] LambertW v0.4.3
[b4fcebef] Lasso v0.5.0
[5078a376] LazyArrays v0.14.10
[e6f89c97] LoggingExtras v0.3.0
[f0e99cf1] MLBase v0.8.0
[1914dd2f] MacroTools v0.5.2
[e1d29d7a] Missings v0.4.3
[bac558e1] OrderedCollections v1.1.0
[90014a1f] PDMats v0.9.10
[69de0a69] Parsers v0.3.10
[f27b6e38] Polynomials v0.6.0
[2dfb63ee] PooledArrays v0.5.2
[1fd47b50] QuadGK v2.1.1
[3cdcf5f2] RecipesBase v0.7.0
[189a3867] Reexport v0.2.0
[79098fc4] Rmath v0.5.1
[1277b4bf] ShiftedArrays v1.0.0
[a2af1166] SortingAlgorithms v0.3.1
[276daf66] SpecialFunctions v0.8.0
[90137ffa] StaticArrays v0.12.1
[2913bbd2] StatsBase v0.32.0
[4c63d2b9] StatsFuns v0.9.0
[3eaba693] StatsModels v0.6.7
[3783bdb8] TableTraits v1.0.0
[bd369af6] Tables v0.2.11
[30578b45] URIParser v0.4.0
[81def892] VersionParsing v1.1.3
[ea10d353] WeakRefStrings v0.6.1
[2a0f44e3] Base64 [`@stdlib/Base64`]
[ade2ca70] Dates [`@stdlib/Dates`]
[8bb1440f] DelimitedFiles [`@stdlib/DelimitedFiles`]
[8ba89e20] Distributed [`@stdlib/Distributed`]
[9fa8497b] Future [`@stdlib/Future`]
[b77e0a4c] InteractiveUtils [`@stdlib/InteractiveUtils`]
[76f85450] LibGit2 [`@stdlib/LibGit2`]
[8f399da3] Libdl [`@stdlib/Libdl`]
[37e2e46d] LinearAlgebra [`@stdlib/LinearAlgebra`]
[56ddb016] Logging [`@stdlib/Logging`]
[d6f4376e] Markdown [`@stdlib/Markdown`]
[a63ad114] Mmap [`@stdlib/Mmap`]
[44cfe95a] Pkg [`@stdlib/Pkg`]
[de0858da] Printf [`@stdlib/Printf`]
[3fa0cd96] REPL [`@stdlib/REPL`]
[9a3f8284] Random [`@stdlib/Random`]
[ea8e919c] SHA [`@stdlib/SHA`]
[9e88b42a] Serialization [`@stdlib/Serialization`]
[1a1011a3] SharedArrays [`@stdlib/SharedArrays`]
[6462fe0b] Sockets [`@stdlib/Sockets`]
[2f01184e] SparseArrays [`@stdlib/SparseArrays`]
[10745b16] Statistics [`@stdlib/Statistics`]
[4607b0f0] SuiteSparse [`@stdlib/SuiteSparse`]
[8dfed614] Test [`@stdlib/Test`]
[cf7118a7] UUIDs [`@stdlib/UUIDs`]
[4ec0a83e] Unicode [`@stdlib/Unicode`]
[ Info: Starting 4 parallel workers for tests...
[ Info: 4 parallel workers started
[ Info: Testing hurdle degenerate cases. The following warnings about step-halving are expected ...
1: λ=0.000386732571607375, pct_dev=6.491976604627858e-6
2: λ=0.00035237631582540674, pct_dev=0.004137275679515495
step-halving because obj=0.004873710484493199 > 0.0048737104844521545 + 5.348152476436496e-15 = length(scratchmu)*eps(objold)
3: λ=0.0003210721751172995, pct_dev=0.007781659027663257
4: λ=0.00029254900799187346, pct_dev=0.011000893812644796
5: λ=0.00026655976042072805, pct_dev=0.01384672457319358
6: λ=0.00024287932597443493, pct_dev=0.01636328834963452
step-halving because obj=0.004853629958394753 > 0.00485362995832963 + 5.348152476436496e-15 = length(scratchmu)*eps(objold)
7: λ=0.00022130259605833834, pct_dev=0.018588564316925682
step-halving because obj=0.004847225402105616 > 0.004847225402075316 + 5.348152476436496e-15 = length(scratchmu)*eps(objold)
8: λ=0.00020164268336002862, pct_dev=0.020555493976648687
step-halving because obj=0.004840589108480022 > 0.004840589108449965 + 5.348152476436496e-15 = length(scratchmu)*eps(objold)
9: λ=0.00018372930312084647, pct_dev=0.022292855685093316
10: λ=0.00016740729821076853, pct_dev=0.023825953055227722
11: λ=0.00015253529523157167, pct_dev=0.02517716069551157
12: λ=0.0001389844800080886, pct_dev=0.026366360317267468
13: λ=0.00012663748186144804, pct_dev=0.027411290020289636
14: λ=0.00011538735700040242, pct_dev=0.02832782749366669
15: λ=0.00010513666222536851, pct_dev=0.029130219588688777
step-halving because obj=0.0047950177502431605 > 0.004795017750074621 + 5.348152476436496e-15 = length(scratchmu)*eps(objold)
16: λ=9.579661092204997e-5, pct_dev=0.029831270237958174
step-halving because obj=0.004789253164598393 > 0.004789253164442045 + 5.348152476436496e-15 = length(scratchmu)*eps(objold)
17: λ=8.728630403425833e-5, pct_dev=0.030442496928184237
step-halving because obj=0.004783753703245748 > 0.004783753703178281 + 5.348152476436496e-15 = length(scratchmu)*eps(objold)
18: λ=7.953202935498933e-5, pct_dev=0.030974261196463515
19: λ=7.246662306655003e-5, pct_dev=0.031435879206021755
20: λ=6.60288879997001e-5, pct_dev=0.03183571788072681
21: λ=6.016306357304766e-5, pct_dev=0.03218127930818637
step-halving because obj=0.004764518539996998 > 0.004764518539672642 + 5.348152476436496e-15 = length(scratchmu)*eps(objold)
22: λ=5.481834282156947e-5, pct_dev=0.03247927557229435
23: λ=4.994843233098504e-5, pct_dev=0.03273569741126037
24: λ=4.5511151266348316e-5, pct_dev=0.03295587690875246
step-halving because obj=0.004752931599085589 > 0.00475293159876313 + 5.348152476436496e-15 = length(scratchmu)*eps(objold)
25: λ=4.1468066021834846e-5, pct_dev=0.033144545621176746
step-halving because obj=0.004749571406770409 > 0.004749571406369983 + 5.348152476436496e-15 = length(scratchmu)*eps(objold)
26: λ=3.778415732723409e-5, pct_dev=0.03330588958302205
27: λ=3.442751692778391e-5, pct_dev=0.033443599554707104
28: λ=3.136907121013224e-5, pct_dev=0.03356091938831385
29: λ=2.8582329380607118e-5, pct_dev=0.03366069162108365
30: λ=2.6043154014634736e-5, pct_dev=0.03374539711868052
31: λ=2.372955198991474e-5, pct_dev=0.033817196120928816
32: λ=2.1621483992516497e-5, pct_dev=0.033877963105122144
33: λ=1.9700690945928288e-5, pct_dev=0.03392931958095369
34: λ=1.795053585967147e-5, pct_dev=0.033972664521059515
35: λ=1.6355859727648175e-5, pct_dev=0.0340092017437984
36: λ=1.4902850228082263e-5, pct_dev=0.03403996415048871
37: λ=1.3578922087795775e-5, pct_dev=0.03406583601656832
38: λ=1.2372608074593485e-5, pct_dev=0.034087572372232255
step-halving because obj=0.0047230553668729195 > 0.004723055366334534 + 5.348152476436496e-15 = length(scratchmu)*eps(objold)
39: λ=1.1273459673583369e-5, pct_dev=0.034105816996643945
step-halving because obj=0.004721965550004314 > 0.004721965549936855 + 5.348152476436496e-15 = length(scratchmu)*eps(objold)
40: λ=1.0271956587139042e-5, pct_dev=0.0341211173866095
41: λ=9.359424274636258e-6, pct_dev=0.0341339379041421
42: λ=8.527958817731798e-6, pct_dev=0.03414467235331431
step-halving because obj=0.004719213180408082 > 0.0047192131803512295 + 5.348152476436496e-15 = length(scratchmu)*eps(objold)
Iteration: 1, deviance: 204.0380396102879, diff.dev.:284.0542927421118
Iteration: 2, deviance: 103.01893015575959, diff.dev.:101.01910945452832
Iteration: 3, deviance: 69.83490468963156, diff.dev.:33.184025466128034
Iteration: 4, deviance: 60.607472505222646, diff.dev.:9.227432184408912
Iteration: 5, deviance: 58.58206318973799, diff.dev.:2.0254093154846586
Iteration: 6, deviance: 58.153700985860056, diff.dev.:0.42836220387793134
Iteration: 7, deviance: 58.09051069340532, diff.dev.:0.06319029245473473
Iteration: 8, deviance: 58.08834852763462, diff.dev.:0.0021621657706987207
Iteration: 9, deviance: 58.088345222699864, diff.dev.:3.3049347578639754e-6
1: λ=0.00038674044876033174, pct_dev=5.408929673822449e-6
2: λ=0.00035238349319380514, pct_dev=0.004046376329978285
3: λ=0.0003210787148680711, pct_dev=0.007611478289555773
4: λ=0.0002925549667692108, pct_dev=0.010760649203050532
5: λ=0.0002665651898367098, pct_dev=0.013544519504385955
6: λ=0.00024288427305606497, pct_dev=0.016006274304332435
7: λ=0.0002213071036548711, pct_dev=0.01818307250563489
8: λ=0.00020164679051410886, pct_dev=0.02010714327092178
9: λ=0.000183733045406678, pct_dev=0.02180664182504133
10: λ=0.000167410708042241, pct_dev=0.023306323185635414
11: λ=0.00015253840214301398, pct_dev=0.024628076465672666
12: λ=0.0001389873109100814, pct_dev=0.02579135132999444
13: λ=0.0001266400612739101, pct_dev=0.026813500399619716
14: λ=0.0001153897072649705, pct_dev=0.027710055819832546
15: λ=0.00010513880369890995, pct_dev=0.028494954136865425
16: λ=9.579856215298414e-5, pct_dev=0.029180720603098842
17: λ=8.728808192321398e-5, pct_dev=0.0297786217165672
18: λ=7.953364930119035e-5, pct_dev=0.030298793003017743
19: λ=7.246809910119532e-5, pct_dev=0.030750347604051487
20: λ=6.60302329074955e-5, pct_dev=0.031141470061326393
21: λ=6.016428900294135e-5, pct_dev=0.0314794987187319
22: λ=5.481945938764883e-5, pct_dev=0.031770999359783225
23: λ=4.994944970441121e-5, pct_dev=0.03202183203722353
24: λ=4.5512078259123385e-5, pct_dev=0.032237212510321744
25: λ=4.146891066312668e-5, pct_dev=0.03242176927755969
26: λ=3.778492693292148e-5, pct_dev=0.03257959685858758
27: λ=3.442821816382316e-5, pct_dev=0.03271430573274792
28: λ=3.136971015029444e-5, pct_dev=0.032829068905250725
29: λ=2.8582911559086306e-5, pct_dev=0.03292666687394974
30: λ=2.604368447398234e-5, pct_dev=0.033009526681117785
31: λ=2.3730035324715953e-5, pct_dev=0.03307976125064971
32: λ=2.1621924389186096e-5, pct_dev=0.03313920409341786
33: λ=1.9701092218971507e-5, pct_dev=0.033189441530157016
34: λ=1.7950901484723522e-5, pct_dev=0.03323184210402219
35: λ=1.63561928715783e-5, pct_dev=0.033267583266010314
36: λ=1.4903153776423796e-5, pct_dev=0.03329767543883244
37: λ=1.3579198669739283e-5, pct_dev=0.03332298359031394
38: λ=1.2372860085759425e-5, pct_dev=0.03334424646583123
39: λ=1.127368929677188e-5, pct_dev=0.0333620936411545
40: λ=1.027216581123637e-5, pct_dev=0.033377060566930905
41: λ=9.359614911841426e-6, pct_dev=0.033389601777973676
42: λ=8.528132519253062e-6, pct_dev=0.03340010243927127
Iteration: 1, deviance: 202.88392988622178, diff.dev.:283.33062895363446
Iteration: 2, deviance: 103.34453979599363, diff.dev.:99.53939009022815
Iteration: 3, deviance: 70.8605677714221, diff.dev.:32.48397202457153
Iteration: 4, deviance: 61.88239574380505, diff.dev.:8.978172027617049
Iteration: 5, deviance: 59.91832501231309, diff.dev.:1.964070731491958
Iteration: 6, deviance: 59.501911842558584, diff.dev.:0.41641316975450593
Iteration: 7, deviance: 59.441417118304834, diff.dev.:0.060494724253750576
Iteration: 8, deviance: 59.43942365499241, diff.dev.:0.001993463312423671
Iteration: 9, deviance: 59.4394208386435, diff.dev.:2.816348910528177e-6
[ Info: Testing dmr degenerate cases. The 2 following warnings by workers are expected ...
┌ Warning: fitgl! failed on count dimension 2 with frequencies OrderedCollections.OrderedDict(0.0 => 200) and will return zero coefs (ErrorException("IRLS failed to converge in 30 iterations at λ = 4.3709033880452197e-7"))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/dmr.jl:412
┌ Warning: fitgl failed for countsj with frequencies OrderedCollections.OrderedDict(0.0 => 200) and will return missing path (ErrorException("IRLS failed to converge in 30 iterations at λ = 4.3709033880452197e-7"))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/dmr.jl:375
[ Info: Testing hdmr degenerate cases. The 2 following warnings by workers are expected ...
┌ Warning: hurdle_regression! failed on count dimension 2 with frequencies OrderedCollections.OrderedDict(0.0 => 200) and will return zero coefs (ErrorException("y is all zeros! There is nothing to explain."))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/hdmr.jl:456
┌ Warning: fit(InclusionRepetition...) failed for countsj with frequencies OrderedCollections.OrderedDict(0.0 => 200) and will return missing path (ErrorException("y is all zeros! There is nothing to explain."))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/hdmr.jl:332
[ Info: Testing hdmr degenerate cases. The 12 following warnings by workers are expected ...
┌ Warning: hurdle_regression! failed on count dimension 2 with frequencies OrderedCollections.OrderedDict(1.0 => 44,2.0 => 29,3.0 => 20,4.0 => 12,5.0 => 13,6.0 => 16,7.0 => 20,8.0 => 14,9.0 => 14,10.0 => 18) and will return zero coefs (LinearAlgebra.PosDefException(1))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/hdmr.jl:456
┌ Warning: hurdle_regression! failed on count dimension 4 with frequencies OrderedCollections.OrderedDict(1.0 => 13,2.0 => 16,3.0 => 35,4.0 => 38,5.0 => 36,6.0 => 29,7.0 => 16,8.0 => 12,9.0 => 5) and will return zero coefs (LinearAlgebra.PosDefException(1))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/hdmr.jl:456
┌ Warning: hurdle_regression! failed on count dimension 3 with frequencies OrderedCollections.OrderedDict(1.0 => 65,2.0 => 52,3.0 => 21,4.0 => 9,5.0 => 12,6.0 => 5,7.0 => 8,8.0 => 9,9.0 => 9,10.0 => 10) and will return zero coefs (LinearAlgebra.PosDefException(1))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/hdmr.jl:456
┌ Warning: hurdle_regression! failed on count dimension 1 with frequencies OrderedCollections.OrderedDict(1.0 => 35,2.0 => 19,3.0 => 21,4.0 => 17,5.0 => 17,6.0 => 20,7.0 => 21,8.0 => 10,9.0 => 14,10.0 => 26) and will return zero coefs (LinearAlgebra.PosDefException(1))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/hdmr.jl:456
┌ Warning: fit(InclusionRepetition...) failed for countsj with frequencies OrderedCollections.OrderedDict(1.0 => 13,2.0 => 16,3.0 => 35,4.0 => 38,5.0 => 36,6.0 => 29,7.0 => 16,8.0 => 12,9.0 => 5) and will return missing path (LinearAlgebra.PosDefException(1))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/hdmr.jl:332
┌ Warning: fit(InclusionRepetition...) failed for countsj with frequencies OrderedCollections.OrderedDict(1.0 => 65,2.0 => 52,3.0 => 21,4.0 => 9,5.0 => 12,6.0 => 5,7.0 => 8,8.0 => 9,9.0 => 9,10.0 => 10) and will return missing path (LinearAlgebra.PosDefException(1))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/hdmr.jl:332
┌ Warning: fit(InclusionRepetition...) failed for countsj with frequencies OrderedCollections.OrderedDict(1.0 => 44,2.0 => 29,3.0 => 20,4.0 => 12,5.0 => 13,6.0 => 16,7.0 => 20,8.0 => 14,9.0 => 14,10.0 => 18) and will return missing path (LinearAlgebra.PosDefException(1))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/hdmr.jl:332
┌ Warning: fit(InclusionRepetition...) failed for countsj with frequencies OrderedCollections.OrderedDict(1.0 => 35,2.0 => 19,3.0 => 21,4.0 => 17,5.0 => 17,6.0 => 20,7.0 => 21,8.0 => 10,9.0 => 14,10.0 => 26) and will return missing path (LinearAlgebra.PosDefException(1))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/hdmr.jl:332
┌ Warning: fit(InclusionRepetition...) failed for countsj with frequencies OrderedCollections.OrderedDict(1.0 => 35,2.0 => 19,3.0 => 21,4.0 => 17,5.0 => 17,6.0 => 20,7.0 => 21,8.0 => 10,9.0 => 14,10.0 => 26) and will return missing path (LinearAlgebra.PosDefException(1))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/hdmr.jl:332
┌ Warning: fit(InclusionRepetition...) failed for countsj with frequencies OrderedCollections.OrderedDict(1.0 => 13,2.0 => 16,3.0 => 35,4.0 => 38,5.0 => 36,6.0 => 29,7.0 => 16,8.0 => 12,9.0 => 5) and will return missing path (LinearAlgebra.PosDefException(1))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/hdmr.jl:332
┌ Warning: fit(InclusionRepetition...) failed for countsj with frequencies OrderedCollections.OrderedDict(1.0 => 44,2.0 => 29,3.0 => 20,4.0 => 12,5.0 => 13,6.0 => 16,7.0 => 20,8.0 => 14,9.0 => 14,10.0 => 18) and will return missing path (LinearAlgebra.PosDefException(1))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/hdmr.jl:332
┌ Warning: fit(InclusionRepetition...) failed for countsj with frequencies OrderedCollections.OrderedDict(1.0 => 65,2.0 => 52,3.0 => 21,4.0 => 9,5.0 => 12,6.0 => 5,7.0 => 8,8.0 => 9,9.0 => 9,10.0 => 10) and will return missing path (LinearAlgebra.PosDefException(1))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/hdmr.jl:332
[ Info: Testing hdmr degenerate cases. The 2 following warnings by workers are expected ...
┌ Warning: hurdle_regression! failed on count dimension 2 with frequencies OrderedCollections.OrderedDict(0.0 => 200) and will return zero coefs (ErrorException("y is all zeros! There is nothing to explain."))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/hdmr.jl:456
┌ Warning: fit(Hurdle...) failed for countsj with frequencies OrderedCollections.OrderedDict(0.0 => 200) and will return missing path (ErrorException("y is all zeros! There is nothing to explain."))
└ @ HurdleDMR ~/.julia/packages/HurdleDMR/9x3Z9/src/hdmr.jl:332
Test Summary: | Pass Total
HurdleDMR | 1303 1303
Testing HurdleDMR tests passed