R Observatory: Metrics for tidyposterior version 1.1.0

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

tidyposterior

1.1.0Package record

Bayesian Analysis to Compare Models using Resampling Statistics

0packages depend

6.9Kdownloads / year

84.7%test coverage

13/13flavors OK

Overview

About

Maintained by Max KuhnCRAN page ↗GitHub ↗Website ↗Issues ↗Declared funder: Posit Software, PBC

Bayesian analysis used here to answer the question: "when looking at resampling results, are the differences between models 'real'?" To answer this, a model can be created were the performance statistic is the resampling statistics (e.g. accuracy or RMSE). These values are explained by the model types. In doing this, we can get parameter estimates for each model's affect on performance and make statistical (and practical) comparisons between models. The methods included here are similar to Benavoli et al (2017) https://jmlr.org/papers/v18/16-305.html.

Changes in 1.1.0

New stan_glmer_inits() computes data-based starting values for the Bayesian models used by perf_mod(). The results can be passed to rstanarm::stan_glmer() (directly or via perf_mod(..., init = )) and can shorten warmup for models that are slow to converge, such as those with heterogeneous variances.
perf_mod() gains an initialize argument (default FALSE) that computes and applies these starting values automatically, reusing the sampler seed (when one is passed) so that the entire fit is reproducible.
Fixed a bug where perf_mod() duplicated the resampling statistics for workflow sets: when more than one metric had been collected, each statistic was included in the Bayesian model once per metric.
New compare_to_leader() contrasts every model in a perf_mod() object against the best model in the set and returns a data frame of probability statements about how much each candidate gives up relative to that leader. autoplot() on the result draws the posterior metric intervals alongside those probabilities.
New initialize_keys() builds a template of model labels to edit and pass to the key argument of compare_to_leader().
perf_mod() gains a select_best argument for workflow sets. Workflows are always reduced to their own best tuning parameter candidate; select_best = TRUE additionally collapses workflows that fit the same type of model with the same engine down to the best of each group, so that each model type/engine combination competes once. The default, FALSE, keeps the existing behavior of one competitor per wflow_id.

From NEWS.md in the release

Install

R (CRAN)pak (dev)Ubuntu (r2u)Fedora (COPR)openSUSE (OBS)

install.packages("tidyposterior", repos = "https://cloud.r-project.org/")

Installs the current CRAN release. Prebuilt binaries on Windows and macOS.

if (!requireNamespace("pak", quietly = TRUE))
  install.packages("pak", repos = "https://cloud.r-project.org/")
pak::pak("tidymodels/tidyposterior")

Development version from tidymodels/tidyposterior. Installs pak first if it is not already available.

Release

# enable cranapt (r2u) if it is not already set up, then install
grep -rqs r2u.stat.illinois.edu /etc/apt/sources.list /etc/apt/sources.list.d/ \
  || curl -fsSL https://raw.githubusercontent.com/eddelbuettel/r2u/master/inst/scripts/add_cranapt_noble.sh | sudo bash
sudo apt install -y r-cran-tidyposterior

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled. We list this channel from recorded r2u download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

bspm (used by r2u) also needs make: sudo apt install make

# enable the iucar/cran COPR if it is not already present, then install
ls /etc/yum.repos.d/*iucar*cran*.repo >/dev/null 2>&1 \
  || sudo dnf copr enable -y iucar/cran
sudo dnf install -y R-CRAN-tidyposterior

RPMs from the iucar/cran COPR, rebuilt from CRAN.

For install.packages() integration in R, also: sudo dnf install R-CoprManager

# add the autoCRAN OBS repo (Tumbleweed) if it is missing, then install
zypper -q lr | grep -qi autoCRAN \
  || sudo zypper addrepo https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/devel:languages:R:autoCRAN.repo
sudo zypper install -y R-tidyposterior

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed). We list this channel from recorded autoCRAN download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

Health

CRAN checks

13OK

CRAN check page ↗

Slowest check: 7.2 min · r-oldrel-windows-x86_64

Status changes

OK13 OK2026-08-04
NOTE12 OK, 1 NOTE2026-08-01
OK13 OK2026-07-29
ERROR12 OK, 1 ERROR2026-07-27
OK13 OK2026-06-09

Show 2 earlier changesHide 2 earlier changes

ERROR12 OK, 1 ERROR2026-06-08
OK14 OK2026-03-10

Advisories

none known

How this is measured·How advisories are found

Documentation

In release 1.1.0

README· In the repository, left out of the releaseVignettesYes · 1 · staticNEWSYes · 100% structured · mentions 1.1.0Citation fileNoWebsiteYes · pkgdown

Help pages: 17 (5 internal)includes a package overview page
Examples that run: 100%10 run in a plain check (3 of them under a condition)
Exported functions with examples: 40%
Documented parameters: 64%
Return-value docs: 60%
Help pages citing references: 6%

Vignettes (1)

Introduction to tidyposterior

How these are measured

Downloads

6.9K

CRAN downloads in the past year

Rank #4,827 · ~19/day · ~573/mo

Releases R versions

Daily download trend is not available in this view yet.

62830 days

1.7K90 days

6.9K1 year

Compare downloads with other packages →

Also on87 r2u6 autocran1.8K conda_forge

How downloads are counted

Repository

tidymodels/tidyposterior ↗Organization: tidymodels

103Stars

15Forks

7Open issues

1Open PRs

7Releases

244Commits

15Commit identities

244 commits · Last activity 2026-09-17 · 0% stars, 30d · Default branch at 1.1.0.9000, ahead of CRAN 1.1.0 (checked 2026-10-11)

Responsiveness

How these are sampled

PRs merged (all time): 98%
Median days to close, 50 most recently updated closed issues: 6
Median days to close, 50 most recently updated closed PRs: 0

Stars over time

2025-05-19 · 1022026-08-05 · 103

How these are measured

PracticesBeta

14 development-tooling and community-health practices detected across 6 families in the upstream repository

Checks run against github.com/tidymodels/tidyposterior on 2026-10-11.

Continuous integration (2)

GitHub ActionsR CMD check workflow

The R CMD check workflow runs on Linux, macOS and Windows, and on R-devel

Governance and community (2)

Code of conductIssue templates

Docs source (4)

README.Rmdpkgdown

GitHub Pages site last deployed 2026-09-17 · The repository has a site deploy workflow

pkgdown site last built 2026-09-02

Coverage (1)

Coverage reporting (Codecov)

Show all practicesHide 2 practices

CRAN release process (1)

revdep/

Lint, format, editor (4)

Lint workflowAirVS CodeRStudio project

How this is detected·Detection ruleset v3 (2026-09-26)

Dependencies

Declared dependencies

21 external dependencies (excludes base and recommended)

Installing tidyposterior adds 155 packages (74 with compiled code, 147 MB of source tarballs). Heaviest: BH 14 MB, stringi 11 MB, ggplot2 6.0 MB.

Depends (1)

R >= 4.1

Imports (15)

dplyr generics ggplot2 patchwork purrr rlang rsample rstanarmstatstibble tidyr tuneutilsvctrs (>= 0.3.0)workflowsets

LinkingTo (0)

none

Suggests (8)

covr knitr parsnip rmarkdown rstan splines2 testthat yardstick

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

0direct

0indirect

Nothing depends on this yet.

How these are counted

Code & Tests

Datasets

People & History

People (2)

Max Kuhn

Author, Maintainer since 0.0.1 (2017)

Posit Software, PBC

Copyright holder, Funder · added in 1.0.1

Listed in earlier versions (1)

RStudio

no longer listed · 0.0.1 to 1.0.0

Releases (8)

Pick two releases to compare their code metrics.

1.1.0Latest
record
2026-09-02 · current release · diff ↗ ·
added 3 exports
compare_to_leader, initialize_keys, stan_glmer_inits
R
R 4.6.0 released · 2026-04-24
1.0.2
record
2025-07-31 · diff ↗
R
R 4.5.0 released · 2025-04-11
R
R 4.4.0 released · 2024-04-24
1.0.1
record
2023-10-11 · diff ↗
R
R 4.3.0 released · 2023-04-21
1.0.0
record
2022-06-23 · diff ↗
R
R 4.2.0 released · 2022-04-22
R
R 4.1.0 released · 2021-05-18
0.1.0
record
2021-03-25 · diff ↗ ·
added 1 export
autoplot
0.0.3
record
2020-06-11 · diff ↗ ·
added 24 exports
vec_cast.data.frame.posterior, vec_cast.data.frame.posterior_diff, vec_cast.posterior.data.frame, vec_cast.posterior.posterior, vec_cast.posterior.tbl_df, vec_cast.posterior_diff.data.frame, vec_cast.posterior_diff.posterior_diff, vec_cast.posterior_diff.tbl_df, vec_cast.tbl_df.posterior, vec_cast.tbl_df.posterior_diff, vec_proxy.posterior, vec_proxy.posterior_diff, vec_ptype2.data.frame.posterior, vec_ptype2.data.frame.posterior_diff, vec_ptype2.posterior.data.frame, vec_ptype2.posterior.posterior, vec_ptype2.posterior.tbl_df, vec_ptype2.posterior_diff.data.frame, vec_ptype2.posterior_diff.posterior_diff, vec_ptype2.posterior_diff.tbl_df, vec_ptype2.tbl_df.posterior, vec_ptype2.tbl_df.posterior_diff, vec_restore.posterior, vec_restore.posterior_diff
R
R 4.0.0 released · 2020-04-24
R
R 3.6.0 released · 2019-04-26
0.0.2
record
2018-11-15 · diff ↗ ·
added 2 exports
tidy, tidy.perf_mod
R
R 3.5.0 released · 2018-04-23

Show 2 earlier eventsHide 2 earlier events

0.0.1
record
2017-11-14
R
R 3.4.0 released · 2017-04-21

Package metadata

First published: 2017-11-14
Total releases: 8 / 9 yrs
License: MIT + file LICENSE OSI · relicensed from GPL-2 in 0.1.0
Minimum R: ≥ 4.1
Bundled data: 185 KB / 5 files
Download size: 307 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("tidyposterior")

Format

Kuhn, M., & Posit Software, PBC. (2026). tidyposterior: Bayesian Analysis to Compare Models using Resampling Statistics (Version 1.1.0) [Computer software]. https://doi.org/10.32614/CRAN.package.tidyposterior

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

Format

APA

Balamuta, J. J. (2026). R Observatory: Metrics for tidyposterior version 1.1.0 [Data set]. HJJB, LLC. Data release v2026-10-17. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-17, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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