FactoMineR (version 1.01)

HMFA: Hierarchical Multiple Factor Analysis

Description

Performs a hierarchical multiple factor analysis, using an object of class list of data.frame.

Usage

HMFA(X,H,type = rep("s", length(H[[1]])), ncp = 5, graph = TRUE)

Arguments

X

a data.frame

H

a list with one vector for each hierarchical level; in each vector the number of variables or the number of group constituting the group

type

the type of variables in each group in the first partition; three possibilities: "c" or "s" for quantitative variables (the difference is that for "s", the variables are scaled in the program), "n" for qualitative variables; by default, all the variabl

ncp

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

graph

boolean, if TRUE a graph is displayed

Value

• Returns a list including:
• eig
  a numeric vector with the all eigenvalues
• group
  a list of matrices with all the results for the groups (Lg and RV coefficients, coordinates, square cosine, contributions, distance to the origin, the correlations between each group and each factor)
• ind
  a list of matrices with all the results for the active individuals (coordinates, square cosine, contributions)
• quanti.var
  a list of matrices with all the results for the quantitative variables (coordinates, correlation between variables and axes)
• quali.var
  a list of matrices with 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)
• partial
  a list of arrays with the coordinates of the partial points for each partition

References

Le Dien, S. & Pag�s, J. (2003) Hierarchical Multiple factor analysis: application to the comparison of sensory profiles, Food Quality and Preferences, 18 (6), 453-464.

Examples

data(wine)
hierar <- list(c(2,5,3,10,9,2), c(4,2))
res.hmfa <- HMFA(wine, H = hierar, type=c("n",rep("s",5)))