Package: rjpdmp
Type: Package
Title: Reversible Jump PDMP Samplers
Version: 2.0.0
Author: Matt Sutton, Augustin Chevalier, Paul Fearnhead, with PolyaGamma simulation code contributed from Jesse Windle and James G. Scott (<https://github.com/jgscott/helloPG>)
Maintainer: Matt Sutton <matt.sutton.stat@gmail.com>
Description: Provides an implementation of the reversible jump piecewise deterministic Markov processes (PDMPs) methods developed in the paper Reversible Jump PDMP Samplers for Variable Selection (Chevallier, Fearnhead, Sutton 2020, <arXiv:2010.11771>). It also contains an implementation of a Gibbs sampler for variable selection in Logistic regression based on Polya-Gamma augmentation.
License: GPL (>= 2)
RoxygenNote: 7.1.1
Encoding: UTF-8
Imports: data.table, Rcpp (>= 0.12.3)
Suggests: MASS
LinkingTo: Rcpp, RcppArmadillo
NeedsCompilation: yes
Packaged: 2022-02-21 22:53:23 UTC; matth
Repository: CRAN
Date/Publication: 2022-02-21 23:10:02 UTC
Built: R 4.0.5; x86_64-apple-darwin17.0; 2022-02-22 11:31:47 UTC; unix
Archs: rjpdmp.so.dSYM
