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)Returns a list including:
a matrix containing all the eigenvalues, the percentage of variance and the cumulative percentage of variance
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))
a list of matrices with all the results for the active individuals (coordinates, square cosine, contributions)
a list of matrices with all the results for the quantitative variables (coordinates, correlation between variables and axes)
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)
a list of arrays with the coordinates of the partial points for each partition
a data.frame
a list with one vector for each hierarchical level; in each vector the number of variables or the number of group constituting the group
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
number of dimensions kept in the results (by default 5)
boolean, if TRUE a graph is displayed
a length 2 vector specifying the components to plot
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)
Sebastien Le, Francois Husson francois.husson@institut-agro.fr
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
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)))
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