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ade4 (version 1.01)

pta: Partial Triadic Analysis of a K-tables

Description

performs a partial triadic analysis of a K-tables, using an object of class ktab.

Usage

pta(X, scannf = TRUE, nf = 2)
plot.pta (x, xax = 1, yax = 2, option = 1:4, ...)
print.pta (x, ...)

Arguments

X
an object of class ktab where the arrays have 1) the same dimensions 2) the same names for columns 3) the same column weightings
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 'pta'
xax, yax
the numbers of the x-axis and the y-axis
option
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 of class 'pta', sub-class of 'dudi' containing :
  • RVa matrix with the all RV coefficients
  • RV.eiga numeric vector with the all eigenvalues (interstructure)
  • RV.cooa data frame with the scores of the arrays
  • tab.namesa vector of characters with the array names
  • nfan integer indicating the number of kept axes
  • rankan integer indicating the rank of the studied matrix
  • tabwa numeric vector with the array weights
  • cwa numeric vector with the column weights
  • lwa numeric vector with the row weights
  • eiga numeric vector with the all eigenvalues (compromis)
  • cos2a numeric vector with the $\cos^2$ between compromise and arrays
  • taba data frame with the modified array
  • lia data frame with the row coordinates
  • l1a data frame with the row normed scores
  • coa data frame with the column coordinates
  • c1a data frame with the column normed scores
  • Tlia data frame with the row coordinates (each table)
  • Tcoa data frame with the column coordinates (each table)
  • Tcompa data frame with the principal components (each table)
  • Taxa data frame with the principal axes (each table)
  • TLa data frame with the factors for Tli
  • TCa data frame with the factors for Tco
  • T4a data frame with the factors for Tax and Tcomp

References

Blanc, L., Chessel, D. and Dol�dec, S. (1998) Etude de la stabilit� temporelle des structures spatiales par Analyse d'une s�rie de tableaux faunistiques totalement appari�s. Bulletin Fran�ais de la P"che et de la Pisciculture, 348, 1--21. Thioulouse, J., and D. Chessel. 1987. Les analyses multi-tableaux en �cologie factorielle. I De la typologie d'�tat � la typologie de fonctionnement par l'analyse triadique. Acta Oecologica, Oecologia Generalis, 8, 463--480.

Examples

Run this code
data(meaudret)
wit1 <- within.pca(meaudret$mil, meaudret$plan$dat, scan = FALSE, 
    scal = "partial")
kta1 <- ktab.within(wit1, colnames = rep(c("S1","S2","S3","S4","S5"), 4))
kta2 <- t(kta1)
pta1 <- pta(kta2, scann = FALSE)
pta1
plot(pta1)

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