README.md

In MarcoDVisser/MCMCR: Markov-chain monte-carlo methods and rejection sampling in R

MCMCR (0.1)

Markov Chain Monte Carlo algorithms and rejection sampling in R. MCMCR provides general-purpose MCMC algorithms for use in R. Algorithms will be optimized for speed and efficiency in general use as this packages continues to develop.

Installation

Currently there isn't a release on CRAN, though one day, when I am statisfied with the optimizations, there may be. You can still download the zip or tar ball. Then decompress and run R CMD INSTALL on it, or use the devtools package to install the development version.

## Make sure your current packages are up to date
update.packages()
## devtools is required
library(devtools)
install_github("MCMCR", "MarcoDVisser")

Examples

 require(MCMCR)

 priors<-function(a){
 a[1]<-runif(1,-1000,1000)
 a[2]<-runif(1,0,1000)
 return(a)
 }

 LL<-function(a,dat){
  dnorm(dat,a[1],a[2],log=TRUE)
 }


 dat<-rnorm(100,20,220)
 results<-rs(dat,c(1,1),LL,priors,N=1000)

Package is being tested.. more to follow

MarcoDVisser/MCMCR documentation built on May 7, 2019, 2:49 p.m.