Abstract
The rjmcmc package for R implements the post-processing reversible jump Markov chain Monte Carlo (MCMC) algorithm of Barker & Link. MCMC output from each of the models is used to estimate posterior model probabilities and Bayes factors. Automatic differentiation is used to simplify implementation. The package is demonstrated on two examples.
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APA
Gelling, N., Schofield, M. R., & Barker, R. J. (2019). R package rjmcmc: reversible jump MCMC using post-processing. Australian and New Zealand Journal of Statistics, 61(2), 189–212. https://doi.org/10.1111/ANZS.12263
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