ade4 (version 1.2-2)

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)
plot.mfa (x, xax = 1, yax = 2, option.plot = 1:4, ...) 
print.mfa (x, ...) 
summary.mfa (object, ...)

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

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

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
• cg
  a data frame with the gravity center for the lisup
• link
  a data frame containing the projected inertia and the links between the arrays and the reference array
• corli
  a data frame giving the correlations between the $lisup and the $li

References

Escofier, B. and Pag�s, 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))