Package: rjmcmc
Type: Package
Title: Reversible-Jump MCMC Using Post-Processing
Version: 0.4.5
Date: 2019-07-07
Authors@R: c(person("Nick", "Gelling", email="nickcjgelling@gmail.com", 
                    role=c("aut","cre")),
             person(c("Matthew", "R."), "Schofield", 
                    email="mschofield@maths.otago.ac.nz", role="aut"),
             person(c("Richard", "J."), "Barker", 
                    email="rbarker@maths.otago.ac.nz", role="aut"))
Description: 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. For a detailed description of
    the package, see Gelling, Schofield & Barker (2019)
    <doi:10.1111/anzs.12263>.
License: GPL-3
Depends: madness, R (>= 3.2.0)
Imports: utils, coda, mvtnorm
Suggests: FSAdata
RoxygenNote: 6.1.0
LazyData: TRUE
NeedsCompilation: no
Packaged: 2019-07-07 00:02:12 UTC; rachaelyoung
Author: Nick Gelling [aut, cre],
  Matthew R. Schofield [aut],
  Richard J. Barker [aut]
Maintainer: Nick Gelling <nickcjgelling@gmail.com>
Repository: CRAN
Date/Publication: 2019-07-09 14:20:02 UTC
Built: R 4.2.0; ; 2022-04-27 00:54:19 UTC; unix
