ENMCA: MCA and cluster analysis

In EnQuireR: A package dedicated to questionnaires

Description

This function allows to perform a cluster analysis following a MCA.

Usage

ENMCA(dataset,ind.sup = NULL, quanti.sup = NULL, quali.sup = NULL, axes = c(1, 2), row.w = NULL,level.ventil = 0,signif=FALSE,proba=0.05,report=FALSE,language="english")

Arguments

dataset	current dataset
ind.sup	a vector indicating the indexes of the supplementary individuals
quanti.sup	a vector indicating the indexes of the supplementary quantitatives variables
quali.sup	a vector indicating the indexes of the supplementary qualitatives variables
axes	a length 2 vector specifying the components to plot
row.w	an optional row weights (by default, uniform row weights)
level.ventil	a number corresponding to the level under which the category is ventilated; by default 0, and no ventilation is done
signif	a logical value. If TRUE, a p-value is associated to the 2 first dimensions
proba	Threshold used for the automatic description of the clusters. By default, proba=0.05
report	a logical value. If TRUE, a pdf report is produced using the Sweave package
language	a value of c("english","french") which determines the language to use for the report

Details

If report=TRUE, a directory named "EnQuireR" is created in your working directory (which can be known thanks to the getwd() function). This directory contains the final pdf report and also the teX file used to produce it.

Value

A list containing the following elements:

data	dataset withe the new categorical variable, obtained with the cluster analysis
catdes	result of the catdes of the clusters
MCA	normal results of an MCA. On the MCA factor map, each cluster is displayed in a different colour

Author(s)

Sebastien Le [e-mail]
Jerome Bouche [e-mail]
Marine Cadoret [e-mail]
Gwenaelle Fournier [e-mail]
Olivier Fournier [e-mail]
Francois Le Poder [e-mail]

Examples

## Not run: 
data(tea)
res.enmca=ENMCA(tea[,1:18])

## End(Not run)

EnQuireR documentation built on May 2, 2019, 5:24 p.m.