mfasenso {SensoMineR}R Documentation

Make MFA (or PCA) with illustrative individuals

Description

Usage

mfasenso(ktab, ktab.illu = NULL, scale.unit = TRUE, nbcoord = 2, 
    poids = NULL)

Arguments

ktab ktableau with active individuals
ktab.illu ktableau with illustrative individuals
scale.unit Boolean, TRUE if the variables are scaled to unit
nbcoord number of coordinates
poids vector of the weight of the variables (by default, all the variables hace the same weight)

Details

Factor analysis is done. Two ktable are required, the first one concern the active individuals, the second one concerns the illustrative individuals. The outputs are the coordinates of the active and illustrative individuals (the mean points and the partial points if the method used is an MFA). If in the ktables, there is only one group of variable, then a PCA is done (else an MFA).

Value

Author(s)

François Husson

References

Escofier B., Pagès J. (1988, 1990, 1993, 1998) Analyses factorielles simples et multiples. Objectifs méthodes et interprétation. Dunod. Paris. Pagès, J. & Husson, F. (2005) Multiple Factor Analysis with confidence ellipses: a useful methodology to study the relations between sensory and instrumental data. Journal of chemometrics.

Examples

 
## PCA 
data(chocolates)
ktab.donnee <- ktab.data.frame(cbind.data.frame(chocolates[,1],
    chocolates[,4], chocolates[,-(1:4)]), blocks = c(2,14),
    tabnames = c("JP","Desc"))

## MFA 
data(chocolates)
ktab.donnee <- ktab.data.frame(cbind.data.frame(chocolates[,1],
    chocolates[,4], chocolates[,-(1:4)]), blocks = c(2,6,8),
    tabnames = c("JP","A-F","T-S"))

[Package SensoMineR version 1.03 Index]