wca: Within-Class Analysis

In ade4: Analysis of Ecological Data: Exploratory and Euclidean Methods in Environmental Sciences

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 [e-mail]

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 documentation built on Feb. 16, 2023, 7:58 p.m.