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stableGR

1.2

A Stable Gelman-Rubin Diagnostic for Markov Chain Monte Carlo

1packages depend
3.2Kdownloads / year
87.0%test coverage
13/13checks pass

Overview

About
Maintained by Christina KnudsonFirst published 2020-03-053 releasesCRAN page ↗

Practitioners of Bayesian statistics often use Markov chain Monte Carlo (MCMC) samplers to sample from a posterior distribution. This package determines whether the MCMC sample is large enough to yield reliable estimates of the target distribution. In particular, this calculates a Gelman-Rubin convergence diagnostic using stable and consistent estimators of Monte Carlo variance. Additionally, this uses the connection between an MCMC sample's effective sample size and the Gelman-Rubin diagnostic to produce a threshold for terminating MCMC simulation. Finally, this informs the user whether enough samples have been collected and (if necessary) estimates the number of samples needed for a desired level of accuracy. The theory underlying these methods can be found in "Revisiting the Gelman-Rubin Diagnostic" by Vats and Knudson (2018) arXiv:1812:09384.

Install

Health

CRAN checks
13OK
Slowest check: 4.1 min · r-devel-windows-x86_64
Code health
Yes
Tests · ratio 1.58
87.0%
Coverage · measured lines
100%
Documentation · exports
2
Dependencies · direct
Check history
  • OK2026-08-04
    13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • NOTE2026-08-01
    12 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • OK2026-03-10
    14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

Documentation
READMENoVignettesNopkgdown siteNoNEWSNoCode of conductNoContributing guideNo
Examples that run
100%
Documented parameters
100%
Return-value docs
100%
References docs
29%

Downloads

3.2K
CRAN downloads in the past year
Rank #16,068 · ~9/day · ~268/mo
Daily download trend is not available in this view yet.
17030 days
66790 days
3.2K1 year
Compare downloads with other packages →
Also on106 r2u10 autocran35 c2d4u

Dependencies

Declared dependencies
2 external dependencies (excludes base and recommended)
Depends (2)
R >= 3.5mcmcse
Imports (1)
LinkingTo (0)
none
Suggests (0)
none
Enhances (0)
none
Reverse dependencies
1direct
0indirect

Code & Tests

Datasets

People & History

People (2)
Maintainer (1)
Author, Maintainer
Authors (2)
Author, Maintainer
Package Timeline

3 releases. Pick two to compare their code metrics. R releases are shown for context.

  • R
    R 4.6.0 released · 2026-04-24
  • R
    R 4.5.0 released · 2025-04-11
  • R
    R 4.4.0 released · 2024-04-24
  • R
    R 4.3.0 released · 2023-04-21
  • 1.2Latest
    2022-10-08 · current release · diff ↗
  • R
    R 4.2.0 released · 2022-04-22
  • 1.1
    2021-10-11 · diff ↗
  • unarchivedReturned to CRAN
    2021-10-11
  • archivedRemoved from CRAN
    2021-10-07
    check problems were not corrected in time
  • R
    R 4.1.0 released · 2021-05-18
  • R
    R 4.0.0 released · 2020-04-24
  • 1.0
    2020-03-05
  • R
    R 3.6.0 released · 2019-04-26

Package metadata

First published
2020-03-05
Total releases
3 / 6 yrs
License
GPL-3 OSI
Minimum R
≥ 3.5
Bundled data
6.5 KB / 1 file
Download size
29 KB
Installed size
not tracked yet
With dependencies
not tracked yet

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("stableGR")
Knudson, C., & Vats, D. (2022). stableGR: A Stable Gelman-Rubin Diagnostic for Markov Chain Monte Carlo (Version 1.2) [Computer software]. https://doi.org/10.32614/CRAN.package.stableGR

This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.

Cite the R Observatory

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

APA

Balamuta, J. J. (2026). R Observatory: Metrics for stableGR version 1.2 [Data set]. HJJB, LLC. Data release v2026-08-13. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-13, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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