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
Browse package contents
Package details |
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| Maintainer | |
| License | GPL-2 | file LICENSE |
| Version | 1.0.0 |
| URL | http://github.com/hjy78/mcmcn |
| Package repository | View on GitHub |
| Installation |
Install the latest version of this package by entering the following in R:
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