initialize-mcmcoutputpermhier-method: Initializer of the 'mcmcoutputpermhier' class

In simonsays1980/finmix: An R package for Bayesian estimation of finite mixture distributions

Description

Only used implicitly. The initializer stores the data into the slots of the passed-in object.

Usage

## S4 method for signature 'mcmcoutputpermhier'
initialize(
  .Object,
  mcmcoutput,
  Mperm = integer(),
  parperm = list(),
  relabel = character(),
  weightperm = array(),
  logperm = list(),
  hyperperm = list(),
  entropyperm = array(),
  STperm = array(),
  Sperm = array(),
  NKperm = array()
)

Arguments

.Object	An object: see the "initialize Methods" section in initialize.
mcmcoutput	An mcmcoutput class containing the results from MCMC sampling.
Mperm	An integer defining the number of permuted MCMC samples.
parperm	A named list containing the permuted component parameter samples from MCMC sampling
relabel	A character specifying the relabeling algorithm used for permuting the MCMC samples.
weightperm	An array of dimension Mperm\ x K containing the relabeled weight parameters.
logperm	A named list containing the mixture log-likelihood, the prior log-likelihood, and the complete data posterior log-likelihood for the permuted MCMC samples.
entropyperm	An array of dimension Mperm\ x 1 containing the entropy for each MCMC permuted draw.
STperm	An array of dimension Mperm\ x 1 containing all permuted MCMC states, for the last observation in slot y of the fdata object passed in to mixturemcmc() where a state is defined for non-Markov models as the last indicator of this observation.
NKperm	An array of dimension MpermxK containing the numbers of observations assigned to each component.
An	array of dimension NxstoreS containing the last storeS permuted indicators. storeS is defined in the slot storeS of the mcmc object passed into mixturemcmc().

See Also

• Classes_Details for details of class definitions, and

• setOldClass for the relation to S3 classes

simonsays1980/finmix documentation built on Dec. 23, 2021, 2:25 a.m.