mcmc: Markov Chain Monte Carlo (original) (raw)
Simulates continuous distributions of random vectors using Markov chain Monte Carlo (MCMC). Users specify the distribution by an R function that evaluates the log unnormalized density. Algorithms are random walk Metropolis algorithm (function metrop), simulated tempering (function temper), and morphometric random walk Metropolis (Johnson and Geyer, 2012, <doi:10.1214/12-AOS1048>, function morph.metrop), which achieves geometric ergodicity by change of variable.
| Version: | 0.9-8 |
|---|---|
| Depends: | R (≥ 3.6.0) |
| Imports: | stats |
| Suggests: | xtable, Iso |
| Published: | 2023-11-16 |
| DOI: | 10.32614/CRAN.package.mcmc |
| Author: | Charles J. Geyer and Leif T. Johnson |
| Maintainer: | Charles J. Geyer |
| License: | MIT + file |
| URL: | http://www.stat.umn.edu/geyer/mcmc/,https://github.com/cjgeyer/mcmc |
| NeedsCompilation: | yes |
| Materials: | |
| In views: | Bayesian |
| CRAN checks: | mcmc results |
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