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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>.
| Version: | 1.2 |
| Depends: | R (≥ 3.5), mcmcse (≥ 1.4-1) |
| Imports: | mvtnorm |
| Published: | 2022-10-07 |
| DOI: | 10.32614/CRAN.package.stableGR |
| Author: | Christina Knudson [aut, cre], Dootika Vats [aut] |
| Maintainer: | Christina Knudson <drchristinaknudson at gmail.com> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| CRAN checks: | stableGR results |
| Reference manual: | stableGR.pdf |
| Package source: | stableGR_1.2.tar.gz |
| Windows binaries: | r-devel: stableGR_1.2.zip, r-release: stableGR_1.2.zip, r-oldrel: stableGR_1.2.zip |
| macOS binaries: | r-release (arm64): stableGR_1.2.tgz, r-oldrel (arm64): stableGR_1.2.tgz, r-release (x86_64): stableGR_1.2.tgz, r-oldrel (x86_64): stableGR_1.2.tgz |
| Old sources: | stableGR archive |
| Reverse imports: | qbld |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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