Dual Multiple Factor Analysis (DMFA)
Performs Dual Multiple Factor Analysis (DMFA) with supplementary individuals, supplementary quantitative variables and supplementary categorical variables.
DMFA(don, num.fact = ncol(don), scale.unit = TRUE, ncp = 5,
quanti.sup = NULL, quali.sup = NULL, graph = TRUE, axes=c(1,2))don |
a data frame with n rows (individuals) and p columns (numeric variables) |
num.fact |
the number of the categorical variable which allows to make the group of individuals |
scale.unit |
a boolean, if TRUE (value set by default) then data are scaled to unit variance |
ncp |
number of dimensions kept in the results (by default 5) |
quanti.sup |
a vector indicating the indexes of the quantitative supplementary variables |
quali.sup |
a vector indicating the indexes of the categorical supplementary variables |
graph |
boolean, if TRUE a graph is displayed |
axes |
a length 2 vector specifying the components to plot |
Returns a list including:
eig |
a matrix containing all the eigenvalues, the percentage of variance and the cumulative percentage of variance |
var |
a list of matrices containing all the results for the active variables (coordinates, correlation between variables and axes, square cosine, contributions) |
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.sup |
a list of matrices containing all the results for the supplementary quantitative variables (coordinates, correlation between variables and axes) |
quali.sup |
a list of matrices containing 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) |
svd |
the result of the singular value decomposition |
var.partiel |
a list with the partial coordinate of the variables for each group |
cor.dim.gr |
|
Xc |
a list with the data centered by group |
group |
a list with the results for the groups (cordinate, normalized coordinates, cos2) |
Cov |
a list with the covariance matrices for each group |
Returns the individuals factor map and the variables factor map.
Francois Husson Francois.Husson@agrocampus-ouest.fr
## Example with the famous Fisher's iris data res.dmfa = DMFA ( iris, num.fact = 5)
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