MFA {FactoMineR} | R Documentation |
Performs Multiple Factor Analysis (MFA) with supplementary individuals and supplementary groups of variables. Groups of variables can be quantitative or qualitative.
MFA (base, group, type = rep("s",length(group)), ind.sup = NULL, ncp = 5, name.group = NULL, num.group.sup = NULL, graph = TRUE, weight.col.mfa = NULL)
base |
a data frame with n rows (individuals) and p columns (variables) |
group |
a list indicating the number of variables in each group |
type |
the type of variables in each group; three possibilities: "c" or "s" for quantitative variables (the difference is that for "s" variables are scaled to unit variance), "n" for qualitative variables; by default, all variables are quantitative and scaled to unit variance |
ind.sup |
a vector indicating the indexes of the supplementary individuals |
ncp |
number of dimensions kept in the results (by default 5) |
name.group |
a vector containing the name of the groups (by default, NULL and the group are named group.1, group.2 and so on) |
num.group.sup |
the indexes of the illustrative groups (by default, NULL and no group are illustrative) |
graph |
boolean, if TRUE a graph is displayed |
weight.col.mfa |
vector of weights, useful for HMFA method (by default, NULL and an MFA is performed) |
summary.quali |
a summary of the results for the qualitative variables |
summary.quanti |
a summary of the results for the quantitative variables |
separate.analyses |
the results for the separate analyses |
eig |
a numeric vector containing all the eigenvalues |
group |
a list of matrices containing 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) |
rapport.inertie |
inertia ratio |
ind |
a list of matrices containing all the results for the active individuals (coordinates, square cosine, contributions) |
ind.sup |
a list of matrices containing all the results for the supplementary individuals (coordinates, square cosine) |
quanti.var |
a list of matrices containing all the results for the quantitative variables (coordinates, correlation between variables and axes) |
quali.var |
a list of matrices containing 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.axes |
a list of matrices containing all the results for the partial axes (coordinates, correlation between variables and axes, correlation between partial axes) |
Returns the individuals factor map, the variables factor map and the
groups factor map.
Jérémy Mazet, François Husson François.Husson@agrocampus-rennes.fr
Escofier, B. and Pagès, J. (1994) Multiple Factor Analysis (AFMULT package), Computational Statistics and Data Analysis, 18, 121-140.
data(wine) aa = MFA(wine, group=c(2,5,3,10,9,2), type=c("n",rep("s",5)), ncp=5, name.group=c("orig","olf","vis","olfag","gust","ens"), num.group.sup=c(1,6)) ## Not run: #### Interactive graph liste = plot.MFApartial(aa) plot(aa,choix="ind",habillage = "quali") ## End(Not run) ###Example 2 data (poison) MFA(poison, group=c(2,2,5,6), type=c("s","n","n","n"), name.group=c("desc","desc2","symptom","eat"), num.group.sup=1:2)