Learn R Programming
mixAK (version 4.2)

NMixCluster: Clustering based on the MCMC output of the mixture model

Description

TO BE ADDED. This function only works for models with a fixed number of mixture components.

Usage

NMixCluster(object, ...)


"NMixCluster"(object, ...)


"NMixCluster"(object, prob = c("poster.comp.prob", "quant.comp.prob", "poster.comp.prob_b", "quant.comp.prob_b", "poster.comp.prob_u"), pquant = 0.5, HPD = FALSE, pHPD = 0.95, pthresh = -1, unclass.na = FALSE, ...)

Arguments

object
an object of apropriate class.
prob
character string which identifies estimates of the component probabilities to be used for clustering.
pquant
when prob is either “quant.comp.prob” or “quant.comp.prob_b”, argument pquant is the probability of the quantile of the component probabilities to be used for clustering.
HPD
logical value. If TRUE then only those subjects are classified for which the lower limit of the pHPD*100% HPD credible interval of the component probability exceeds the value of ptrash.
pHPD
credible level of the HPD credible interval, see argument HPD.
pthresh
an optional threshold for the estimated component probability (when HPD is FALSE) or for the lower limit of the HPD credible interval (when HPD is TRUE) to classify a subject. No effect when pthresh is negative.
unclass.na
logical value taken into account when pthresh is positive. If unclass.na is TRUE, unclassified subjects get classification NA. If unclass.na is FALSE, unclassified subjects create a separate (last) group.
...
optional additional arguments.

Value

A data.frame with three (when HPD is FALSE) or five (when HPD is TRUE) columns.

See Also

NMixMCMC, GLMM_MCMC.

Examples

Run this code
## TO BE ADDED.

Run the code above in your browser using DataLab