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runjags

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

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.

Functions (23)

add.summary

Summary statistics and plot methods for runjags class objects

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

combine.mcmc

Combining and dividing runjags and MCMC objects

dump.list.format

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

extract.runjags

Extract peripheral information from runjags objects

findjags

Attempt to Locate a JAGS Install

load.runjagsmodule

Load the internal JAGS module provided by runjags

mutate.functions

Mutate functions to be used with runjags summary methods

new_unique

Create a Unique Filename

read.jagsfile

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

results.jags

Importing of saved JAGS simulations with partial error recovery

run.jags

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

run.jags.study

Drop-k and simulated dataset studies using JAGS

runjags-class

The runjags class and available S3 methods

runjags-package

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

runjags.options

Options for the runjags package

runjags.printmethods

Print methods for runjags helper classes

template.jags

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

template_huiwalter

Create a Hui-Walter model based on paired test data for an arbitrary number of tests and populations

testjags

Analyse the System to Check That JAGS Is Installed

timestring

Calculate the Elapsed Time in Sensible Units

write.jagsfile

Write a complete JAGS model to a text file

runjags

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

v2.2.0-2

GPL-2

Authors

Matthew Denwood [aut, cre], Martyn Plummer [cph] (Copyright holder of the code in src/distributions/DPar1.*, configure.ac, R/rjags_functions.R, and original copyright holder of some modified code where indicated)

Initial release

2021-03-01

runjags

Functions (23)

runjags

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