Package index • rjags

All functions
`adapt()`	Adaptive phase for JAGS models
`coda.samples()`	Generate posterior samples in mcmc.list format
`list.factories()` `set.factory()`	Advanced control over JAGS
`dic.samples()`	Generate penalized deviance samples
`-` `diffdic()`	Differences in penalized deviance
`jags.model()`	Create a JAGS model object
`load.module()` `unload.module()` `list.modules()`	Dynamically load JAGS modules
`coef(<jags>)` `variable.names(<jags>)` `list.samplers()`	Functions for manipulating jags model objects
`jags.samples()`	Generate posterior samples
`jags.version()`	JAGS version
`LINE`	Linear regression example
`summary(<mcarray>)` `print(<mcarray>)` `as.mcmc.list(<mcarray>)`	Objects for representing MCMC output
`parallel.seeds()`	Get initial values for parallel RNGs
`read.jagsdata()` `read.bugsdata()`	Read data files for jags models
`read.data()`	Deprecated Functions in the rjags package
`rjags-package` `rjags`	Bayesian graphical models using MCMC
`update(<jags>)`	Update jags models

Reference