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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.
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Package details |
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| Author | Rodrigo Fonseca Villa [aut, cre] (ORCID: <https://orcid.org/0009-0005-2938-2270>) |
| Maintainer | Rodrigo Fonseca Villa <rodrigo03.villa@gmail.com> |
| License | GPL-3 |
| Version | 2.0.1 |
| URL | https://github.com/rodrigosqrt3/Rtwalk |
| Package repository | View on CRAN |
| Installation |
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