Rtwalk: An MCMC Sampler Using the t-Walk Algorithm

Implements the t-walk algorithm, a general-purpose, self-adjusting Markov Chain Monte Carlo (MCMC) sampler for continuous distributions as described by Christen & Fox (2010) <doi:10.1214/10-BA603>. The t-walk requires no tuning and is robust for a wide range of target distributions, including high-dimensional and multimodal problems. This implementation includes an option for running multiple chains in parallel to accelerate sampling and facilitate convergence diagnostics.

Version:	2.0.0
Imports:	parallel, stats, utils
Suggests:	mvtnorm, coda, devtools, roxygen2, knitr, rmarkdown, ellipse, ggplot2, ggthemes, gridExtra, reshape2, viridis
Published:	2026-02-02
DOI:	10.32614/CRAN.package.Rtwalk
Author:	Rodrigo Fonseca Villa [aut, cre]
Maintainer:	Rodrigo Fonseca Villa <rodrigo03.villa at gmail.com>
BugReports:	https://github.com/rodrigosqrt3/Rtwalk/issues
License:	GPL-3
URL:	https://github.com/rodrigosqrt3/Rtwalk
NeedsCompilation:	no
Materials:	README, NEWS
CRAN checks:	Rtwalk results

Documentation:

Reference manual:	Rtwalk.html , Rtwalk.pdf
Vignettes:	Validation and Simulation Study (source, R code)

Downloads:

Package source:	Rtwalk_2.0.0.tar.gz
Windows binaries:	r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries:	r-release (arm64): Rtwalk_2.0.0.tgz, r-oldrel (arm64): Rtwalk_2.0.0.tgz, r-release (x86_64): Rtwalk_2.0.0.tgz, r-oldrel (x86_64): Rtwalk_2.0.0.tgz
Old sources:	Rtwalk archive

Linking:

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