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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.

Versions across snapshots

VersionRepositoryFileSize
2.0.1 rolling linux/jammy R-4.5 Rtwalk_2.0.1.tar.gz 147.8 KiB
2.0.1 rolling linux/noble R-4.5 Rtwalk_2.0.1.tar.gz 147.6 KiB
2.0.1 rolling source/ R- Rtwalk_2.0.1.tar.gz 106.6 KiB
2.0.1 latest linux/jammy R-4.5 Rtwalk_2.0.1.tar.gz 147.8 KiB
2.0.1 latest linux/noble R-4.5 Rtwalk_2.0.1.tar.gz 147.6 KiB
2.0.1 latest source/ R- Rtwalk_2.0.1.tar.gz 106.6 KiB
2.0.1 2026-04-26 source/ R- Rtwalk_2.0.1.tar.gz 106.6 KiB
2.0.1 2026-04-23 source/ R- Rtwalk_2.0.1.tar.gz 106.6 KiB
2.0.1 2026-04-09 windows/windows R-4.5 Rtwalk_2.0.1.zip 150.7 KiB
1.8.0 2025-04-20 source/ R- Rtwalk_1.8.0.tar.gz 9.3 KiB

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