HMFA {FactoMineR} R Documentation

## 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,
axes = c(1,2), name.group = NULL)


### 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 categorical variables; by default, all the variables are quantitative and the variables are scaled unit ncp number of dimensions kept in the results (by default 5) graph boolean, if TRUE a graph is displayed axes a length 2 vector specifying the components to plot name.group a list of vector containing the name of the groups for each level of the hierarchy (by default, NULL and the group are named L1.G1, L1.G2 and so on)

### Value

Returns a list including:

 eig a matrix containing all the eigenvalues, the percentage of variance and the cumulative percentage of variance group a list with first a list of matrices with the coordinates of the groups for each level and second a matrix with the canonical correlation (correlation between the coordinates of the individuals and the partial points)) 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 categorical 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

### Author(s)

Sebastien Le, Francois Husson francois.husson@institut-agro.fr

### References

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

print.HMFA, plot.HMFA, dimdesc