HMFA function

Hierarchical Multiple Factor Analysis

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

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)

Returns

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

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.

Author(s)

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

See Also

print.HMFA, plot.HMFA, dimdesc

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)))