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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

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