rjmcmc (0.2.2)

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Reversible-Jump MCMC Using Post-Processing.

http://cran.r-project.org/web/packages/rjmcmc

Performs reversible-jump MCMC (Green, 1995) , specifically the restriction introduced by Barker & Link (2013) . 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.

Maintainer: Nick Gelling
Author(s): Nick Gelling [aut, cre], Matthew R. Schofield [aut], Richard J. Barker [aut]

License: GPL-3

Uses: coda, madness, R2jags, knitr

Released 2 months ago.


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