Bump the all-julia-packages group across 1 directory with 7 updates

[dependabot]

Updates the requirements on Base64, StatsFuns, SHA, Printf, LinearAlgebra, PosteriorDB and Distributed to permit the latest version.
Updates Base64 to
Updates StatsFuns to 2.2.1

Release notes

Sourced from StatsFuns's releases.

v2.2.1

StatsFuns v2.2.1

Diff since v2.2.0

Merged pull requests:

• Replace CompatHelper with Dependabot for Julia packages (#213) (@​devmotion)
• Bump codecov/codecov-action from 6 to 7 (#216) (@​dependabot[bot])
• Bump actions/checkout from 6 to 7 (#217) (@​dependabot[bot])
• Avoid Int overflow in signrank and wilcox by normalising in place (#221) (@​andreasnoack)
• Bump version from 2.2.0 to 2.2.1 (#222) (@​devmotion)

Closed issues:

• Arguments typed as Number (#38)
• Dependency load order in StatsFuns 2.x exhausts static TLS on old glibc (libgomp fails to load) (#218)
• signrankcdf returns silently invalid probabilities from n = 72 (Int overflow in signrankDP) (#219)
• wilcoxcdf returns silently invalid probabilities for large samples (Int overflow in wilcox_partitions) (#220)

Commits

• 6f54423 Bump version from 2.2.0 to 2.2.1 (#222)
• fefa6fe Avoid Int overflow in signrank and wilcox by normalising in place (#221)
• a8032c7 Replace CompatHelper with dependabot (#213)
• e6b1781 Bump actions/checkout from 6 to 7 (#217)
• 5bc8a07 Bump codecov/codecov-action from 6 to 7 (#216)
• 5568af3 add owens_t function (#214)
• f8d7f5b CompatHelper: bump compat for LogExpFunctions to 1, (keep existing compat) (#...
• 21903f7 Fix srdist by passing nranges=1 to Rmath.ptukey/qtukey (#211)
• 53dc188 Bump julia-actions/setup-julia from 2 to 3 (#210)
• 37d3c86 Bump julia-actions/cache from 2 to 3 (#208)
• Additional commits viewable in compare view

Updates SHA to
Updates Printf to
Updates LinearAlgebra to
Updates PosteriorDB to 0.7.0

Release notes

Sourced from PosteriorDB's releases.

v0.7.0

Features

• feat: Update posteriordb artifact to 1.1.0 (#48) (013cf84) - github-actions[bot]

Full Changelog: sethaxen/PosteriorDB.jl@v0.6.4...v0.7.0

Commits

• 013cf84 feat: Update posteriordb artifact to 1.1.0 (#48)
• 160ee34 feat: Add PyMC support (#53)
• 99cca61 docs: bump julia-actions/julia-downgrade-compat from 2.6.2 to 2.7.0 (#47)
• bd4e35c chore: modernize package structure (#49)
• 5ef8028 fix: load expected file from zip archives (#50)
• 193f37f docs: bump julia-actions/julia-downgrade-compat from 2 to 2.6.2 (#46)
• 7047190 ci: split downgrade testing into its own workflow (#42)
• 10bff5d ci: modernize TagBot workflow (#44)
• 1eb0ade fix: Bump Compat compat floor (#43)
• 05928b1 docs: Add missing docs dep compat entries (#41)
• Additional commits viewable in compare view

Updates Distributed to

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[github-actions]

DynamicPPL.jl documentation for PR #1508 is available at:
https://TuringLang.github.io/DynamicPPL.jl/previews/PR1508/

[github-actions]

Benchmarks @ 0d06c27

Performance Ratio: gradient time divided by log-density time.

For very small models these ratios are noisy across runs and machines; raw primal and gradient timings are more reliable. The benchmarks are aimed at DynamicPPL developers and mainly catch obvious allocation or type-stability regressions. See benchmark notes for details.

===================================================================================================
                                               eval                       gradient                 
                                            ----------  -------------------------------------------
Model                        dim    linked      primal     FwdDiff    RvsDiff    Mooncake    Enzyme
---------------------------------------------------------------------------------------------------
Simple assume observe*         1     false     2.84 ns       11.73    1161.19       10.68      9.80
Simple assume observe*         1      true     2.91 ns       11.60    1281.67       10.97      9.55
Smorgasbord                  201     false     3.17 μs       82.73     122.76        5.20      8.21
Smorgasbord                  201      true     3.65 μs       95.66     141.85        6.03      6.14
Loop univariate 1k          1000     false     7.93 μs     1364.79     341.61        3.84      9.42
Loop univariate 1k          1000      true     9.96 μs     1460.53     272.19        2.86      7.37
Multivariate 1k             1000     false    698.0 ns     3029.97     714.06        1.39      9.74
Multivariate 1k             1000      true    660.0 ns     3140.49     682.64        1.57     10.55
Loop univariate 10k        10000     false     76.4 μs    30285.75     387.15        3.92      9.03
Loop univariate 10k        10000      true     96.8 μs    26451.93     316.73        2.88      7.21
Multivariate 10k           10000     false     5.25 μs    66347.17     986.74        1.22     10.22
Multivariate 10k           10000      true     5.07 μs    81615.08    1041.91        1.18     10.10
Dynamic                       15     false    738.0 ns         err      68.08       12.26       err
Dynamic                       10      true    971.0 ns        1.66      80.74        7.88       err
Submodel*                      1     false     2.84 ns       11.74    1160.85       11.70      9.74
Submodel*                      1      true     2.84 ns       11.66    1218.94       10.70      9.80
LDA                            6      true     2.11 μs        1.31       7.81       27.31     72.44
===================================================================================================

Main @ 13dd27f

===================================================================================================
                                               eval                       gradient                 
                                            ----------  -------------------------------------------
Model                        dim    linked      primal     FwdDiff    RvsDiff    Mooncake    Enzyme
---------------------------------------------------------------------------------------------------
Simple assume observe*         1     false     5.87 ns        8.94    1260.74        9.73      7.27
Simple assume observe*         1      true     5.87 ns        9.51    1275.21        9.35      7.28
Smorgasbord                  201     false     5.38 μs       70.04     146.35        6.00      8.41
Smorgasbord                  201      true     6.46 μs       74.48     168.08        6.04      5.61
Loop univariate 1k          1000     false     17.0 μs      769.41     320.92        3.01      6.78
Loop univariate 1k          1000      true     18.4 μs     1306.19     286.33        2.85      6.20
Multivariate 1k             1000     false    964.0 ns     1482.98    1106.06        1.92      9.86
Multivariate 1k             1000      true     1.08 μs     1180.01     699.62        1.66     10.10
Loop univariate 10k        10000     false    163.0 μs    21075.82     353.88        3.03      7.09
Loop univariate 10k        10000      true    178.0 μs    24281.37     329.00        2.71      6.57
Multivariate 10k           10000     false     8.66 μs    26200.79    1095.69        1.62      8.55
Multivariate 10k           10000      true     9.39 μs    25045.51    1093.71        1.64      7.83
Dynamic                       15     false      1.3 μs         err      56.37       15.84       err
Dynamic                       10      true     1.72 μs        1.84      60.27       18.35       err
Submodel*                      1     false     5.57 ns        9.02    1225.83        9.53      7.69
Submodel*                      1      true     5.57 ns        9.11    1338.26        9.58      7.77
LDA                            6      true     4.17 μs        1.31       8.96       31.28     28.83
===================================================================================================

Environment

Julia Version 1.13.0
Commit d1c37793dd2 (2026-09-09 19:00 UTC)
Build Info:
  Official https://julialang.org release
Platform Info:
  OS: Linux (x86_64-linux-gnu)
  CPU: 4 × AMD EPYC 9V45 96-Core Processor
  WORD_SIZE: 64
  LLVM: libLLVM-20.1.8 (ORCJIT, znver5)
  GC: Built with stock GC
Threads: 1 default, 1 interactive, 1 GC (on 4 virtual cores)