ade4 (version 1.7-22)

mfa: Multiple Factorial Analysis

Description

performs a multiple factorial analysis, using an object of class ktab.

Usage

mfa(X, option = c("lambda1", "inertia", "uniform", "internal"), 
    scannf = TRUE, nf = 3)
# S3 method for mfa
plot(x, xax = 1, yax = 2, option.plot = 1:4, ...) 
# S3 method for mfa
print(x, ...) 
# S3 method for mfa
summary(object, ...)

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

Arguments

X

K-tables, 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

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

x, object

an object of class 'mfa'

xax, yax

the numbers of the x-axis and the y-axis

option.plot

an integer between 1 and 4, otherwise the 4 components of the plot are displayed

...

further arguments passed to or from other methods

Author

Daniel Chessel
Anne-Béatrice Dufour

References

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

Examples

data(friday87)
w1 <- data.frame(scale(friday87$fau, scal = FALSE))
w2 <- ktab.data.frame(w1, friday87$fau.blo, 
    tabnames = friday87$tab.names)
mfa1 <- mfa(w2, scann = FALSE)
mfa1
plot(mfa1)

data(escopage)
w <- data.frame(scale(escopage$tab))
w <- ktab.data.frame(w, escopage$blo, tabnames = escopage$tab.names)
plot(mfa(w, scann = FALSE))