Generalized Gelman-Rubin Diagnostic and Effective Sample Size for MCMC
Overview
Provides generalized univariate and multivariate 'Gelman-Rubin' convergence diagnostics, effective sample size ('ESS') estimates, and principled termination thresholds for Markov chain Monte Carlo ('MCMC') simulations, based on Vats and Knudson (2021) doi:10.1214/20-STS812. The package incorporates replicated lugsail batch means variance estimators to construct stable convergence statistics for single and multiple chains. Additionally, it offers comprehensive tools for evaluating 'MCMC' output generated from user-supplied probability density functions ('PDF') or log-likelihoods, including implementations for censored data models under right, left, interval, 'Type-I', 'Type-II', progressive, and hybrid censoring schemes.
Install
Health
- OK13 OK2026-09-08
- ERROR12 OK, 1 ERROR2026-09-07
- OK8 OK2026-08-06
Documentation
- Help pages
- 11 (2 internal)
- Examples that run
- 100%6 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 27%
Downloads
Dependencies
Installing LugsailGR adds no packages beyond those that come with R.
Code & Tests
Datasets
People & History
- 0.1.0Latestfirst seen 2026-08-05 · current release
- RR 4.6.0 released · 2026-04-24
Package metadata
- First seen
- 2026-08-05
- Total releases
- 1 / 1 yrs
- License
- GPL (>= 2) OSI
- Minimum R
- ≥ 3.5.0
- Bundled data
- 1.0 KB / 1 file
- Download size
- 16 KB
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