afmult {SensoMineR}R Documentation

Multiple Factor Analysis

Description

Performs a multiple factor analysis, using an object of class ktab.

Usage

afmult(X, option = c("lambda1", "inertia", "uniform", "internal"),
     coord = c(1,2), scannf = TRUE, nf = 3, cex = 0.8, 
     col = "steelblue4", font = 2, clabel = 0.8, scale.unit = TRUE)

Arguments

X an object of class ktab
option a string of characters for the weighting of arrays options:
lambda1
weighting of group k by the inverse of the first eigenvalue of the k analysis
inertia
weighting of group k by the inverse of the total inertia of the array k
uniform
uniform weighting of groups
internal
weighting included in X$tabw
coord a length 2 vector specifying the components to plot
scannf a logical value indicating whether the eigenvalues bar plot should be displayed
nf if scannf FALSE, an integer indicating the number of kept axes
cex cf. function par in the graphics package
col cf. function par in the graphics package
font cf. function par in the graphics package
clabel cf. the ade4 package
scale.unit a boolean, if TRUE (value set by default) then data are scaled to unit variance

Details

The only difference between this function and the mfa programed by Daniel Chessel lies in the calculations of the coordinates of the partial individuals.

Value

Returns a list including:

tab a data frame with the modified array
rank a vector of ranks for the analyses
eig a numeric vector with the all eigenvalues
li a data frame with the coordinates of rows
TL a data frame with the factors associated to the rows (indicators of table)
co a data frame with the coordinates of columns
TC a data frame with the factors associated to the columns (indicators of table)
blo a vector indicating the number of variables for each table
lisup a data frame with the projections of normalized scores of rows for each table
link a data frame containing the projected inertia and the links between the arrays and the reference array

Author(s)

Daniel Chessel chessel@biomserv.univ-lyon1.fr

References

Escofier, B. and Pagès, J. (1994) Multiple factor analysis (AFMULT package), Computational Statistics and Data Analysis, 18, 121–140.

Examples

data(sensopanels)
resafmult<-afmult(ktab.data.frame(sensopanels, blocks = rep(14,7)),
    scannf = FALSE)

[Package SensoMineR version 1.01 Index]