FactoMineR (version 1.02)

AFDM: Multiple Factor Analysis for Mixed Data

Description

Performs Multiple Factor Analysis with both quantitative and qualitative data.

Usage

AFDM (base, type, ncp = 5, graph = TRUE, sup.var = NULL, 
    ind.sup = NULL)

Arguments

base

a data frame with n rows (individuals) and p columns

type

a vector indicating the type of each variable (the length of type must be equal to the number of columns of X

ncp

number of dimensions kept in the results (by default 5)

graph

boolean, if TRUE a graph is displayed

ind.sup

a vector indicating the indexes of the supplementary individuals

sup.var

a vector indicating the indexes of the supplementary variables

Value

• Returns a list including:
• eig
  a numeric vector containing all the eigenvalues
• link.group
• group
• ind
  a list of matrices with all the results for the individuals (coordinates, square cosine, contributions)
• quali.var
  a list of matrices with all the results for the qualitative variables (coordinates, square cosine, contributions, v.test)
• quanti.var
  a list of matrices with all the results for the quantitative variables (coordinates, correlation, square cosine, contributions)
• call
  a list with some statistics
• Returns the individuals factor map.

References

Pag�s J. (2004). Analyse factorielle de donn�es mixtes. Revue Statistique Appliqu�e. LII (4). pp. 93-111.

See Also

print.AFDM, plot.AFDM

Examples

data(wine)
res.afdm = AFDM(wine[,c(1,2,30,31)],type=c("n","n","s","s"))