DiscriMiner (version 0.1-29)

easyMCA: Multiple Correspondence Analysis

Description

Performs a basic Multiple Correspondence Analysis (MCA)

Usage

easyMCA(variables)

Arguments

variables

data frame with categorical variables (coded as factors)

Value

An object of class "qualmca", basically a list with the following elements:

values

table with eigenvalues

coefficients

coefficients of factorial axes

components

factor coordinates

References

Lebart L., Piron M., Morineau A. (2006) Statistique Exploratoire Multidimensionnelle. Dunod, Paris.

Saporta G. (2006) Probabilites, analyse des donnees et statistique. Editions Technip, Paris.

See Also

disqual, binarize

Examples

## Not run: 
#   # load insurance wines dataset
#   data(insurance)
# 
#   # multiple correspondence analysis
#   mca1 = easyMCA(insurance[,-1])
#   mca1
#   ## End(Not run)