hjy78/mcmcn: Markov Chain Monte Carlo Sampler

Simulates continuous distributions of random vectors using Markov chain Monte Carlo (MCMC). Users specify the distribution by an R function that evaluates the unnormalized density. Algorithms are random walk Metropolis algorithm (function mtrp), independence sampler algorithm (function mtrp_exp and mtrp_unif), Metropolis-Hastings algorithm (function mtrp_expu) and Gibbs sampler algorithm (function gibbs_norm and gibbs_multinom).

Getting started

Package details

LicenseGPL-2 | file LICENSE
URL http://github.com/hjy78/mcmcn
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
hjy78/mcmcn documentation built on Jan. 1, 2020, 1:03 p.m.