HMFA {FactoMineR} | R Documentation |
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)
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 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 |
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 |
Sébastien Lê, François Husson
Le Dien, S. & Pagès, J. (2003) Hierarchical Multiple factor analysis: application to the comparison of sensory profiles, Food Quality and Preferences, 18 (6), 453-464.
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)))