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