runjags: Interface Utilities, Model Templates, Parallel Computing...

Description Details References See Also Examples

Description

User-friendly interface utilities for MCMC models via Just Another Gibbs Sampler, facilitating the use of parallel (or distributed) processors for multiple chains, automated control of convergence and sample length diagnostics, and evaluation of the performance of a model using drop-k validation or against simulated data. Template model specifications can be generated using a standard lme4-style formula interface to assist users less familiar with the BUGS syntax. A JAGS extension module provides additional distributions including the Pareto family of distributions, the DuMouchel prior and the half-Cauchy prior.

Details

Just Another Gibbs Sampler (JAGS) is a program which allows analysis of Bayesian models using Markov chain Monte Carlo (MCMC) simulation, and was developed by Martyn Plummer to be an alternative to BUGS that ran on UNIX systems as well as Windows systems. This package is intended to provide additional functions to help automate the process of running models, including convergence diagnostics, collation and plotting of results, and convinience wrappers for running models (either individually or for multiple data sets) over parallel processors and distributed computing clusters.

The package also includes a JAGS extension module providing additional distributions - for more details see the runjags vignettes (links in the examples below). A standalone version of this JAGS module (as well as a version of the runjags package without this module included) is available from the runjags sourceforge page at: https://sourceforge.net/projects/runjags/

References

M. J. Denwood, "runjags: An R Package Providing Interface utilities, model templates, parallel computing methods and additional distributions for MCMC models in JAGS." Journal of Statistical Software, [In review].

See Also

run.jags and extend.jags for basic model runs

runjags-class for S3 methods relating to runjags objects, incluing conversion to/from jags objects (for compatibility with the rjags package)

runjags.options for ways to set default options for runjags functions

jags.model in the rjags package for fine control over the JAGS libraries

Examples

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
	
	## Not run: 
	# A quick-start vignette:
	vignette('quickjags', package='runjags')
	
	# A more comprehensive user guide:
	vignette('userguide', package='runjags')
	
	# For information on how to cite runjags:
	citation('runjags')
	
## End(Not run)
	

runjags documentation built on March 26, 2020, 9:24 p.m.

Related to runjags in runjags...