R: Within-Class Analysis

wca {ade4} | R Documentation

## 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)

[Package ade4 version 1.7-19 Index]