Multiple Factorial Analysis

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, ...)

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

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

References

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

Author

Daniel Chessel
Anne-Béatrice Dufour anne-beatrice.dufour@univ-lyon1.fr

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
#> Multiple Factorial Analysis
#> list of class mfa list of class list
#> $call: mfa(X = w2, scannf = FALSE)
#> $nf: 3 axis-components saved
#> 
#>   vector     length mode      content      
#> 1 $tab.names 10     character tab names    
#> 2 $blo       10     numeric   column number
#> 3 $rank      1      numeric   tab rank     
#> 4 $eig       15     numeric   eigen values 
#> 5 $lw        16     numeric   row weights  
#> 6 $tabw      0      NULL      array weights
#> 
#>    data.frame nrow ncol content                        
#> 1  $tab       16   91   modified array                 
#> 2  $li        16   3    row coordinates                
#> 3  $l1        16   3    row normed scores              
#> 4  $co        91   3    column coordinates             
#> 5  $c1        91   3    column normed scores           
#> 6  $lisup     160  3    row coordinates from each table
#> 7  $TL        160  2    factors for li l1              
#> 8  $TC        91   2    factors for co c1              
#> 9  $T4        40   2    factors for T4comp             
#> 10 $T4comp    40   3    component projection           
#> 11 $link      10   3    link array-total               
#> other elements: NULL
plot(mfa1)
#> Error in eval(thecall$fac, envir = sys.frame(sys.nframe() + pos)): object 'mfa1' not found

data(escopage)
w <- data.frame(scale(escopage$tab))
w <- ktab.data.frame(w, escopage$blo, tabnames = escopage$tab.names)
plot(mfa(w, scann = FALSE))
#> Error in eval(thecall$fac, envir = sys.frame(sys.nframe() + pos)): object 'w' not found