Volume 61, Issue 2
Original Article

R package rjmcmc: reversible jump MCMC using post‐processing

Nicholas Gelling

Corresponding Author

E-mail address: nickcjgelling@gmail.com

Department of Mathematics and Statistics, University of Otago, P.O. Box 56, Dunedin , 9016 New Zealand

Author to whom correspondence should be addressed.Search for more papers by this author
Matthew R. Schofield

E-mail address: nickcjgelling@gmail.com

Department of Mathematics and Statistics, University of Otago, P.O. Box 56, Dunedin , 9016 New Zealand

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Richard J. Barker

E-mail address: nickcjgelling@gmail.com

Department of Mathematics and Statistics, University of Otago, P.O. Box 56, Dunedin , 9016 New Zealand

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First published: 05 July 2019

Summary

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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