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: | 0.9-7 |
| Depends: | R (≥ 3.0.2) |
| Imports: | stats |
| Suggests: | xtable, Iso |
| Published: | 2020-03-21 |
| Author: | Charles J. Geyer and Leif T. Johnson |
| Maintainer: | Charles J. Geyer <charlie at stat.umn.edu> |
| License: | MIT + file LICENSE |
| URL: | http://www.stat.umn.edu/geyer/mcmc/, https://github.com/cjgeyer/mcmc |
| NeedsCompilation: | yes |
| Materials: | ChangeLog |
| In views: | Bayesian |
| CRAN checks: | mcmc results |
| Reference manual: | mcmc.pdf |
| Vignettes: |
Bayes Factors via Serial Tempering Debugging MCMC Code MCMC Example MCMC Morph Example |
| Package source: | mcmc_0.9-7.tar.gz |
| Windows binaries: | r-devel: mcmc_0.9-7.zip, r-release: mcmc_0.9-7.zip, r-oldrel: mcmc_0.9-7.zip |
| macOS binaries: | r-release (arm64): mcmc_0.9-7.tgz, r-oldrel (arm64): mcmc_0.9-7.tgz, r-release (x86_64): mcmc_0.9-7.tgz, r-oldrel (x86_64): mcmc_0.9-7.tgz |
| Old sources: | mcmc archive |
| Reverse depends: | ltbayes |
| Reverse imports: | MCMCpack, nse, prefeR |
| Reverse suggests: | ConnMatTools, fmcmc, MSGARCH, pse |
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