https://github.com/kisungyou/samcpack

Stochastic Approximation Monte Carlo (SAMC) Sampler and Methods
https://github.com/kisungyou/samcpack

bayesian-inference mcmc mcmc-sampler

Last synced: 7 days ago
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Stochastic Approximation Monte Carlo (SAMC) Sampler and Methods

• Host: GitHub
• URL: https://github.com/kisungyou/samcpack
• Owner: kisungyou
• Created: 2018-09-04T03:59:35.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2020-05-08T01:37:54.000Z (over 4 years ago)
• Last Synced: 2024-11-13T18:39:41.130Z (2 months ago)
• Topics: bayesian-inference, mcmc, mcmc-sampler
• Language: C++
• Homepage: https://CRAN.R-project.org/package=SAMCpack
• Size: 22.1 MB
• Stars: 2
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.Rmd
  • Changelog: NEWS.md

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# SAMCpack: Stochastic Approximation Monte Carlo (SAMC) Sampler and Methods

[![CRAN_Status_Badge](http://www.r-pkg.org/badges/version/SAMCpack?color=green)](https://CRAN.R-project.org/package=SAMCpack)

[![Travis build status](https://travis-ci.org/kyoustat/SAMCpack.svg?branch=master)](https://travis-ci.org/kyoustat/SAMCpack)

[![](https://cranlogs.r-pkg.org/badges/SAMCpack)](https://cran.r-project.org/package=SAMCpack)

Stochastic Approximation Monte Carlo (SAMC) is one of the celebrated Markov chain Monte Carlo (MCMC) algorithms. It is known to be capable of sampling from multimodal or doubly intractable distributions. We provide generic SAMC samplers for continuous distributions. User-specified densities in R and C++ are both supported. We also provide functions for specific problems that exploit SAMC computation. 

## Installation

You can install the released version of SAMCpack from [CRAN](https://CRAN.R-project.org) with:

``` r

install.packages("SAMCpack")

```

or the development version from github:

```r

## install.packages("devtools")

devtools::install_github("kyoustat/SAMCpack")

```