c(person("Nick", "Gelling", email="nick_gelling@hotmail.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"))

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"))

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>.

Matt Sutton, Augustin Chevalier, Paul Fearnhead, with PolyaGamma simulation code contributed from Jesse Windle and James G. Scott (<https://github.com/jgscott/helloPG>)
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.

person("Bobby", "Ingram",
email = "ingram.bob@gmail.com",
role = c("aut", "cre"))
Implementation of the Johnson Quantile-Parameterised Distribution in R.
The Johnson Quantile-Parameterised Distribution (J-QPD) is a flexible distribution
system that is parameterised by a symmetric percentile triplet of quantile values
(typically the 10th-50th-90th) along with known support bounds for the distribution.
The J-QPD system was developed by Hadlock and Bickel (2017) <doi:10.1287/deca.2016.0343>.
This package implements the density, quantile, CDF and random number generator functions.