dataR2C

A data frame or a matrix with the number of columns equal to $number(variables)*ploidy$.

The number of unordered observations represented by a string in <code>xdata</code>. For example, for genotypic data from diploid individual, $ploidy = 2$ : two columns for one variable.

ploidy


<code>dataR2C(x, ploidy)</code> returns a list.


An implementation of a variable selection procedure in clustering by mixture models for discrete data (clustMMDD). Genotype data are examples of such data with two unordered observations (alleles) at each locus for diploid individual. The two-fold problem of variable selection and clustering is seen as a model selection problem where competing models are characterized by the number of clusters K, and the subset S of clustering variables. Competing models are compared by penalized maximum likelihood criteria. We considered asymptotic criteria such as Akaike and Bayesian Information criteria, and a family of penalized criteria with penalty function to be data driven calibrated.

Wilson Toussile

ClustMMDD

Variable Selection in Clustering by Mixture Models for Discrete
Data

dataR2C function

Transform a (normal) data frame to be compatible with <code><a rd-options='' href='ClustMMDD'>ClustMMDD</a></code> main functions

Transform a (normal) data frame to be compatible with <code><a rd-options="" href="/link/ClustMMDD?package=ClustMMDD&version=1.0.4" data-mini-rdoc="ClustMMDD::ClustMMDD">ClustMMDD</a></code> main functions

dataR2C: Transform a (normal) data frame to be compatible with `ClustMMDD` main functions

Description

Usage

Arguments

Value

See Also

Examples