ade4 (version 1.6-2)

foucart: K-tables Correspondence Analysis with the same rows and the same columns

Description

K tables have the same rows and the same columns. Each table is transformed by P = X/sum(X). The average of P is computing. A correspondence analysis is realized on this average. The initial rows and the initial columns are projected in supplementary elements.

Usage

foucart(X, scannf = TRUE, nf = 2)
## S3 method for class 'foucart':
plot(x, xax = 1, yax = 2, clab = 1, csub = 2, 
    possub = "bottomright", \dots) 
## S3 method for class 'foucart':
print(x, \dots)

Arguments

X

a list of data frame where the row names and the column names are the same for each table

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

an object of class 'foucart'

xax

the column number of the x-axis

yax

the column number of the y-axis

clab

if not NULL, a character size for the labels, used with par("cex")*clab

csub

a character size for the legend, used with par("cex")*csub

possub

a string of characters indicating the sub-title position ("topleft", "topright", "bottomleft", "bottomright")

...

further arguments passed to or from other methods

Value

• foucart returns a list of the classes 'dudi', 'coa' and 'foucart'
• call
  origine
• nf
  axes-components saved
• rank
  rank
• blo
  useful vector
• cw
  vector: column weights
• lw
  vector: row weights
• eig
  vector: eigen values
• tab
  data.frame: modified array
• li
  data.frame: row coordinates
• l1
  data.frame: row normed scores
• co
  data.frame: column coordinates
• c1
  data.frame: column normed scores
• Tli
  data.frame: row coordinates (each table)
• Tco
  data.frame: col coordinates (each table)
• TL
  data.frame: factors for Tli
• TC
  data.frame: factors for Tco

References

Foucart, T. (1984) Analyse factorielle de tableaux multiples, Masson, Paris.

Examples

data(bf88)
fou1 <- foucart(bf88, scann = FALSE, nf = 3)
fou1
plot(fou1)

data(meaudret)
l1 <- split(meaudret$spe, meaudret$design$season)
l1 <- lapply(l1, function(x) 
    {row.names(x) <- paste("Sit",1:5,sep="");x})
fou2 <- foucart(l1, scan = FALSE)
kplot(fou2, clab.r = 2)