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stableGR
View on CRAN: Click
here
Download and install stableGR package within the R console
Install from CRAN:
install.packages("stableGR")
Install from Github:
library("remotes")
install_github("cran/stableGR") Install by package version:
library("remotes")
install_version("stableGR", "1.2") Attach the package and use:
library("stableGR")
Maintained by
Christina Knudson
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[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-03-05
Latest Update: 2022-10-07
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 collectedand (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 andKnudson (2018) <arXiv:1812:09384>.
How to cite:
Christina Knudson (2020). stableGR: A Stable Gelman-Rubin Diagnostic for Markov Chain Monte Carlo. R package version 1.2, https://cran.r-project.org/web/packages/stableGR. Accessed 25 Jun. 2026.
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Complete documentation for stableGR
Functions, R codes and Examples using
the stableGR R package
Some associated functions: asym.var . mvn.gibbs . n.eff . stable.GR . stableGR-package . target.psrf . titanic.complete .
Some associated R codes: asym.var.R . getT.R . gettau.R . mcmcchecks.R . mvn.gibbs.R . n.eff.R . s.hat.R . size.and.trim.R . stable.GR.R . target.psrf.R . Full stableGR package functions and examples
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