ade4: wca – R documentation

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wca

Within-Class Analysis

Description

Performs a particular case of an Orthogonal Principal Component Analysis with respect to Instrumental Variables (orthopcaiv), in which there is only a single factor as covariable.

Usage

## S3 method for class 'dudi'
wca(x, fac, scannf = TRUE, nf = 2, ...)

Arguments

`x`	a duality diagram, object of class `dudi` from one of the functions `dudi.coa`, `dudi.pca`,...
`fac`	a factor partitioning the rows of `dudi$tab` in classes
`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
`...`	further arguments passed to or from other methods

Value

Returns a list of the sub-class within in the class dudi

`tab`	a data frame containing the transformed data (substraction of the class mean)
`call`	the matching call
`nf`	number of kept axes
`rank`	the rank of the analysis
`ratio`	percentage of within-class inertia
`eig`	a numeric vector containing the eigenvalues
`lw`	a numeric vector of row weigths
`cw`	a numeric vector of column weigths
`tabw`	a numeric vector of class weigths
`fac`	the factor defining the classes
`li`	data frame row coordinates
`l1`	data frame row normed scores
`co`	data frame column coordinates
`c1`	data frame column normed scores
`ls`	data frame supplementary row coordinates
`as`	data frame inertia axis onto within axis

Note

To avoid conflict names with the base:::within function, the function within is now deprecated and removed. It is replaced by the method wca.dudi of the new generic wca function.

Author(s)

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

References

Benzécri, J. P. (1983) Analyse de l'inertie intra-classe par l'analyse d'un tableau de correspondances. Les Cahiers de l'Analyse des données, 8, 351–358.

Dolédec, S. and Chessel, D. (1987) Rythmes saisonniers et composantes stationnelles en milieu aquatique I- Description d'un plan d'observations complet par projection de variables. Acta Oecologica, Oecologia Generalis, 8, 3, 403–426.

Examples

data(meaudret)
pca1 <- dudi.pca(meaudret$env, scan = FALSE, nf = 4)
wit1 <- wca(pca1, meaudret$design$site, scan = FALSE, nf = 2)

if(adegraphicsLoaded()) {
  g1 <- s.traject(pca1$li, meaudret$design$site, psub.text = "Principal Component Analysis", 
    plines.lty = 1:nlevels(meaudret$design$site), psub.cex = 1.5, plot = FALSE)
  g2 <- s.traject(wit1$li, meaudret$design$site, 
    psub.text = "Within site Principal Component Analysis", 
    plines.lty = 1:nlevels(meaudret$design$site), psub.cex = 1.5, plot = FALSE)
  g3 <- s.corcircle (wit1$as, plot = FALSE)
  G <- ADEgS(list(g1, g2, g3), layout = c(2, 2))
  
} else {
  par(mfrow = c(2, 2))
  s.traject(pca1$li, meaudret$design$site, sub = "Principal Component Analysis", csub = 1.5)
  s.traject(wit1$li, meaudret$design$site, sub = "Within site Principal Component Analysis", 
    csub = 1.5)
  s.corcircle (wit1$as)
  par(mfrow = c(1,1))
}
plot(wit1)

ade4

Analysis of Ecological Data: Exploratory and Euclidean Methods in Environmental Sciences

v1.7-16

GPL (>= 2)

Authors

Stéphane Dray <stephane.dray@univ-lyon1.fr>, Anne-Béatrice Dufour <anne-beatrice.dufour@univ-lyon1.fr>, and Jean Thioulouse <jean.thioulouse@univ-lyon1.fr>, with contributions from Thibaut Jombart, Sandrine Pavoine, Jean R. Lobry, Sébastien Ollier, Daniel Borcard, Pierre Legendre, Stéphanie Bougeard and Aurélie Siberchicot. Based on earlier work by Daniel Chessel.

Initial release

wca