CRAN/E | ClustMMDD

ClustMMDD

Variable Selection in Clustering by Mixture Models for Discrete Data

Installation

About

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.

Citation ClustMMDD citation info

Key Metrics

Version 1.0.4
R ≥ 3.0.0
Published 2016-05-30 2882 days ago
Needs compilation? yes
License GPL-2
License GPL-3
CRAN checks ClustMMDD results

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Maintainer

Maintainer

Wilson Toussile

wilson.toussile@gmail.com

Authors

Wilson Toussile

Material

Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

ClustMMDD archive

Depends

Rcpp ≥ 0.11.5
R ≥ 3.0.0

Imports

methods

LinkingTo

Rcpp