Man pages for ClustMMDD
Variable Selection in Clustering by Mixture Models for Discrete Data

backward.explorerGather a set of the most competitive models.
ClustMMDD-package'ClustMMDD' : Clustering by Mixture Models for Discrete Data.
cutEachColRetrieve data from strings in the dataset.
dataR2CTransform a (normal) data frame to be compatible with...
dimJump.RData driven calibration of the penalty function
em.cluster.RCompute estimates of the parameters by Expectation and...
EmOptionsDisplay the current Expectation and Maximization options.
exModelKSAn example of 'modelKS'.
genotype1'genotype1' is a data frame of genotype data with 'ploidy =...
genotype2A genotype data frame compatible with 'ClustMMDD' main...
genotype2_ExploredModelsA data frame of competing models gathered by...
is.element-methodsCheck if a 'modelKS' object is in a set of such objects.
isInFile.RFind a model in a file.
is.modelKS-methodsIs an object from class 'modelKS'?
modelKS-class'modelKS' is a class of parameters of (K, S) model.
model-methodsRetrieve a list of model <=ft(K,S\right) from a 'modelKS'...
model.selection.RSelection of both the number K of clusters and the subset S...
Rcpp_modules_examplesFunctions and Objects created by Rcpp Modules Example
read.modelKS-methodsRead the parameters of a model <=ft(K,S\right) from a file.
read.or.computeRead a given model from a file or compute the estimates of...
selectK.RSelection of the number K of clusters.
setEmOptionsSet Expectation and Maximization options.
setModelKS-methodsSet an instance of class 'modelKS' from a list.
show-methods'show' method for an object of class 'modelKS'
simulData-methodsSimulate a dataset from a given set of parameters in an...
z==-methodsMethods for Function '=='
z[_--methodsGet or set a slot from 'modelKS'.
z[-methodsGet a slot from 'modelKS'.
ClustMMDD documentation built on May 2, 2019, 2:44 p.m.