ClusVis (version 1.2.0)

clusvisVarSelLCM: This function estimates the parameters used for visualization of model-based clustering performs with R package Rmixmod. To achieve the parameter infernece, it automatically samples probabilities of classification from the model parameters

Description

This function estimates the parameters used for visualization of model-based clustering performs with R package Rmixmod. To achieve the parameter infernece, it automatically samples probabilities of classification from the model parameters

Usage

clusvisVarSelLCM(varselResult, sample.size = 5000, maxit = 10^3,
  nbrandomInit = 4 * varselResult@model@g, nbcpu = 1, loccont = NULL)

Arguments

varselResult

['>VSLCMresults] It is an instance of class VSLCMresults returned by function VarSelCluster of R package VarSelLCM.

sample.size

numeric. Number of probabilities of classification sampled for parameter inference.

maxit

numeric. It limits the number of iterations for the Quasi-Newton algorithm (default 1000).

nbrandomInit

numeric. It defines the number of random initialization of the Quasi-Newton algorithm.

nbcpu

numeric. It specifies the number of CPU (only for linux).

loccont

numeric. Index of the column containing continuous variables (only for mixed-type data).

Value

Returns a list

Examples

# NOT RUN {
 # Package loading
 require(VarSelLCM)

 # Data loading (categorical data)
 data("heart")
 # Model-based clustering with 3 components
 res <- VarSelCluster(heart[,-13], 3)

 # Inference of the parameters used for results visualization
 # (specific for VarSelLCM results)
 # It is better because probabilities of classification are generated
 # by using the model parameters
 resvisu <- clusvisVarSelLCM(res)

 # Component interpretation graph
 plotDensityClusVisu(resvisu)

 # Scatter-plot of the observation memberships
 plotDensityClusVisu(resvisu,  add.obs = TRUE)

# }