dic.samples
(Package: rjags) :
Generate penalized deviance samples
Function to extract random samples of the penalized deviance from a jags model.
● Data Source:
CranContrib
● Keywords: models
● Alias: dic, dic.samples
●
0 images
|
coda.samples
(Package: rjags) :
Generate posterior samples in mcmc.list format
This is a wrapper function for jags.samples which sets a trace monitor for all requested nodes, updates the model, and coerces the output to a single mcmc.list object.
● Data Source:
CranContrib
● Keywords: models
● Alias: coda.samples
●
0 images
|
read.jagsdata
(Package: rjags) :
Read data files for jags models
Read data for a JAGS model from a file.
● Data Source:
CranContrib
● Keywords: file
● Alias: read.bugsdata, read.jagsdata
●
0 images
|
adapt
(Package: rjags) :
Adaptive phase for JAGS models
Update the model in adaptive mode.
● Data Source:
CranContrib
● Keywords: models
● Alias: adapt
●
0 images
|
|
The rjags package provides an interface from R to the JAGS library for Bayesian data analysis. JAGS uses Markov Chain Monte Carlo (MCMC) to generate a sequence of dependent samples from the posterior distribution of the parameters.
● Data Source:
CranContrib
● Keywords: package
● Alias: rjags, rjags-package
●
0 images
|
update
(Package: rjags) :
Update jags models
Update the Markov chain associated with the model.
● Data Source:
CranContrib
● Keywords: models
● Alias: update.jags
●
0 images
|
parallel
(Package: rjags) :
Get initial values for parallel RNGs
On a multi-processor system, you may wish to run parallel chains using multiple jags.model objects, each running a single chain on a separate processor. This function returns a list of values that may be used to initialize the random number generator of each chain.
● Data Source:
CranContrib
● Keywords: models
● Alias: parallel.seeds
●
0 images
|
mcarray.object
(Package: rjags) :
Objects for representing MCMC output
An mcarray object is used by the jags.samples function to represent MCMC output from a JAGS model. It is an array with named dimensions, for which the dimensions "iteration" and "chain" have a special status
● Data Source:
CranContrib
● Keywords: models
● Alias: as.mcmc.list.mcarray, mcarray.object, print.mcarray, summary.mcarray
●
0 images
|
jags.object
(Package: rjags) :
Functions for manipulating jags model objects
A jags object represents a Bayesian graphical model described using the BUGS language.
● Data Source:
CranContrib
● Keywords:
● Alias: coef.jags, list.samplers, variable.names.jags
●
0 images
|
diffdic
(Package: rjags) :
Differences in penalized deviance
Compare two models by the difference of two dic objects.
● Data Source:
CranContrib
● Keywords: models
● Alias: diffdic
●
0 images
|
providing 
.