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
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2026-10-04 07:22:36 UTC; root
Author: Christina Knudson [aut, cre], Dootika Vats [aut]
Config/pak/sysreqs: cmake libfftw3-dev make libuv1-dev
Repository: https://knudson1.r-universe.dev
Date/Publication: 2022-10-07 21:50:02 UTC
RemoteUrl: https://github.com/cran/stableGR
RemoteRef: HEAD
RemoteSha: 6972621044a920c0df1f79e08944e796b8b9d3ac