R package `MCMCvis` now on CRAN

October 10, 2016
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(This article was first published on R – Lynch Lab, and kindly contributed to R-bloggers)

MCMCvis, an R package for visualizing, manipulating, and summarizing MCMC output is now available on CRAN!

It can be installed with: install.packages('MCMCvis')

The vignette (tutorial) can be run with: vignette('MCMCvis')

MCMCvis was designed to perform key functions for MCMC analysis using minimal code, in order to free up time/brainpower for interpretation of analysis results. Functions support simple and straightforward subsetting of model parameters within the calls, and produce presentable and ‘publication-ready’ output. Model output can be from JAGS, Stan, or other MCMC samplers. The package deals with different data types behind the scenes so you don’t have to think about it. You can specify which parameters you want to visualize or extract within the functions.

For example, this plot can be made using just one line of code (after loading package/data, of course)!

library('MCMCvis') #load package

data(MCMC_data) #load example data

MCMCplot(MCMC_data, params = 'beta') #create plot

 

rplot02

More information can be found within the package vignette. The package was created and authored by Lynch Lab PhD candidate, Casey Youngflesh. He can be found here on Github and here on Twitter.

To leave a comment for the author, please follow the link and comment on their blog: R – Lynch Lab.

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