DMFA function

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))

Arguments

• 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

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.

Author(s)

Francois Husson francois.husson@institut-agro.fr

See Also

plot.DMFA, dimdesc

Examples

## Example with the famous Fisher's iris data
res.dmfa = DMFA ( iris, num.fact = 5)