Performs reversible-jump Markov chain Monte Carlo (Green, 1995) <doi:10.2307/2337340>, specifically the restriction introduced by Barker & Link (2013) <doi:10.1080/00031305.2013.791644>. By utilising a 'universal parameter' space, RJMCMC is treated as a Gibbs sampling problem. Previously-calculated posterior distributions are used to quickly estimate posterior model probabilities. Jacobian matrices are found using automatic differentiation.
|Author||Nick Gelling [aut, cre], Matthew R. Schofield [aut], Richard J. Barker [aut]|
|Maintainer||Nick Gelling <[email protected]>|
|Package repository||View on CRAN|
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