clusvisMixmod: This function estimates the parameters used for visualization...

In ClusVis: Gaussian-Based Visualization of Gaussian and Non-Gaussian Model-Based Clustering

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

clusvisMixmod(mixmodResult, sample.size = 5000, maxit = 10^3,
  nbrandomInit = 4 * mixmodResult@bestResult@nbCluster, nbcpu = 1,
  loccont = NULL)

Arguments

mixmodResult	[MixmodCluster] It is an instance of class MixmodCluster returned by function mixmodCluster of R package Rmixmod.
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(Rmixmod)

# Data loading (categorical data)
data(birds)

# Model-based clustering with 3 components
resmixmod <- mixmodCluster(birds, 3)

# Inference of the parameters used for results visualization
# (specific for Rmixmod results)
resvisu <- clusvisMixmod(resmixmod)

# Component interpretation graph
plotDensityClusVisu(resvisu)

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

## End(Not run)

ClusVis documentation built on May 2, 2019, 5:21 p.m.