DMFA {FactoMineR}R Documentation

Dual Multiple Factor Analysis (DMFA)

Description

Performs Dual Multiple Factor Analysis (DMFA) with supplementary individuals, supplementary quantitative variables and supplementary qualitative variables.

Usage

DMFA(don, num.fact = ncol(data), scale.unit = TRUE, ncp = 5, 
    quanti.sup = NULL, quali.sup = NULL, graph = TRUE, axes=c(1,2))

Arguments

don a data frame with n rows (individuals) and p columns (numeric variables)
num.fact the number of the qualitative variable which allows to make the group of individuals
scale.unit a boolean, if TRUE (value set by default) then data are scaled to unit variance
ncp number of dimensions kept in the results (by default 5)
quanti.sup a vector indicating the indexes of the quantitative supplementary variables
quali.sup a vector indicating the indexes of the qualitative supplementary variables
graph boolean, if TRUE a graph is displayed
axes a length 2 vector specifying the components to plot

Value

Returns a list including:

eig a matrix containing all the eigenvalues, the percentage of variance and the cumulative percentage of variance
var a list of matrices containing all the results for the active variables (coordinates, correlation between variables and axes, square cosine, contributions)
ind a list of matrices containing all the results for the active individuals (coordinates, square cosine, contributions)
ind.sup a list of matrices containing all the results for the supplementary individuals (coordinates, square cosine)
quanti.sup a list of matrices containing all the results for the supplementary quantitative variables (coordinates, correlation between variables and axes)
quali.sup a list of matrices containing all the results for the supplementary qualitative variables (coordinates of each categories of each variables, and v.test which is a criterion with a Normal distribution)


Returns the individuals factor map and the variables factor map.

Author(s)

Francois Husson Francois.Husson@agrocampus-ouest.fr

See Also

plot.DMFA, dimdesc

Examples

## Example with the famous Fisher's iris data
res.dmfa = DMFA ( iris, num.fact = 5)

[Package FactoMineR version 1.10 Index]