Package: stableGR
Type: Package
Title: A Stable Gelman-Rubin Diagnostic for Markov Chain Monte Carlo
Version: 1.2
Date: 2022-10-7
Authors@R: c(person("Christina", "Knudson", role = c("aut", "cre"),
    email = "drchristinaknudson@gmail.com"), person("Dootika", "Vats", role = c("aut"), email = "dootika.vats@gmail.com"))
Maintainer: Christina Knudson <drchristinaknudson@gmail.com>
Description: 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>. 
License: GPL-3
Depends: R (>= 3.5), mcmcse(>= 1.4-1)
Imports: mvtnorm
ByteCompile: TRUE
Repository: CRAN
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2022-10-07 21:11:40 UTC; christina.knudson
Author: Christina Knudson [aut, cre],
  Dootika Vats [aut]
Date/Publication: 2022-10-07 22:50:02 UTC
Built: R 4.6.0; ; 2026-04-25 19:26:55 UTC; unix
