poissonconsulting/jaggernaut: Bayesian Analyses using 'JAGS'
Version 2.5.2

Facilitates Bayesian analyses using 'JAGS' (Just Another Gibbs Sampler). Key features include the conversion of a data frame into a suitable format for input into 'JAGS'; the option to manually or automatically increase the length of the 'MCMC' (Markov Chain Monte Carlo) chains until convergence is achieved; the option to run 'MCMC' chains on separate processes; the ability to extract derived parameters including posterior predictive checks from an existing model using 'BUGS' code (in the 'JAGS' dialect) without additional 'MCMC' sampling; simple generation of data frames quantifying the effect (and effect size) of particular variables with the other variables held constant.

Getting started

Package details

Maintainer
LicenseMIT + file LICENSE
Version2.5.2
URL https://github.com/poissonconsulting/jaggernaut
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("devtools")
library(devtools)
install_github("poissonconsulting/jaggernaut")
poissonconsulting/jaggernaut documentation built on Sept. 7, 2017, 1:54 p.m.