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runjags (version 2.0.4-6)

Interface Utilities, Model Templates, Parallel Computing Methods and Additional Distributions for MCMC Models in JAGS

Description

User-friendly interface utilities for MCMC models via Just Another Gibbs Sampler (JAGS), 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.

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Version

Install

install.packages('runjags')

Monthly Downloads

8,766

Version

2.0.4-6

License

GPL-2

Maintainer

Matthew Denwood

Last Published

December 17th, 2019

Functions in runjags (2.0.4-6)

new_unique

Create a Unique Filename
extract.runjags

Extract peripheral information from runjags objects
combine.mcmc

Combining and dividing runjags and MCMC objects
load.runjagsmodule

Load the internal JAGS module provided by runjags
findjags

Attempt to Locate a JAGS Install
add.summary

Summary statistics and plot methods for runjags class objects
dump.format

Conversion Between a Named List and a Character String in the R Dump Format
mutate.functions

Mutate functions to be used with runjags summary methods
ask

Obtain Input from User With Error Handling
autorun.jags

Run or extend a user-specified Bayesian MCMC model in JAGS with automatically calculated run-length and convergence diagnostics
read.jagsfile

Extract Any Models, Data, Monitored Variables or Initial Values As Character Vectors from a JAGS or WinBUGS Format Textfile
runjags

Interface Utilities, Model Templates, Parallel Computing Methods and Additional Distributions for MCMC Models in JAGS
runjags-class

The runjags class and available S3 methods
template.jags

Generate a generalised linear mixed model (GLMM) specification in JAGS
testjags

Analyse the System to Check That JAGS Is Installed
results.jags

Importing of saved JAGS simulations with partial error recovery
run.jags.study

Drop-k and simulated dataset studies using JAGS
run.jags

Run or extend a user-specified Bayesian MCMC model in JAGS from within R
timestring

Calculate the Elapsed Time in Sensible Units
runjags.printmethods

Print methods for runjags helper classes
write.jagsfile

Write a complete JAGS model to a text file
runjags.options

Options for the runjags package
xgrid.run.jags

Run a JAGS Model using an Apple Xgrid distributed computing cluster from Within R
xgrid.run

Remote execution of user-specified R functions on Apple Xgrid distributed computing clusters