rjmcmc {rjmcmc}

The rjmcmc Package

Description

Performs reversible-jump MCMC (Green, 1995), specifically the reformulation introduced by Barker & Link (2013). Using a 'universal parameter' space, RJMCMC is treated as Gibbs sampling making it simpler to implement. The required Jacobian matrices are calculated automatically, utilising the madness package.

Functions

rjmcmcpost defaultpost adiff getsampler

Methods

rjmethods

References

Green, P. J. (1995) Reversible jump Markov chain Monte Carlo computation and Bayesian model determination. Biometrika, 711-732.

Barker, R. J. and Link, W. A. (2013) Bayesian multimodel inference by RJMCMC: A Gibbs sampling approach. The American Statistician, 67(3), 150-156.