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mcmc: Markov Chain Monte Carlo
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.
Getting started
Browse package contents
Package details |
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| Author | Charles J. Geyer <geyer@umn.edu> and Leif T. Johnson <ltjohnson@google.com> |
| Maintainer | Charles J. Geyer <geyer@umn.edu> |
| License | MIT + file LICENSE |
| Version | 0.9-8 |
| URL | http://www.stat.umn.edu/geyer/mcmc/ https://github.com/cjgeyer/mcmc |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
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