CMD + K

r-mcmc

Community

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, <https://doi.org/10.1214/12-AOS1048>, function morph.metrop), which achieves geometric ergodicity by change of variable.

Installation

To install this package, run one of the following:

Conda
$conda install conda-forge::r-mcmc

Usage Tracking

0.9_8
0.9_7
0.9_6.1
0.9_6
0.9_5
5 / 8 versions selected
Downloads (Last 6 months): 0

About

Summary

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, <https://doi.org/10.1214/12-AOS1048>, function morph.metrop), which achieves geometric ergodicity by change of variable.

Last Updated

Feb 19, 2020 at 07:22

License

MIT

Supported Platforms

linux-64
macOS-64
win-64

Unsupported Platforms

macOS-arm64 Last supported version: 0.9_8
linux-ppc64le Last supported version: 0.9_8
linux-aarch64 Last supported version: 0.9_8