World

bla1

bla2

hello

Rcpp_Num-class

Rcpp_World-class

Rcpp_vec-class

C++Object-class


  These function and objects are accessible from R via the Rcpp Modules mechanism
  which creates them based on the declaration in the C++ file.  


Rcpp Modules Examples

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

Rcpp Modules Examples function


  Functions and Objects created by Rcpp Modules Example


Rcpp Modules Examples: Functions and Objects created by Rcpp Modules Example

Description

Arguments

See Also