ade4: witwit.coa – R documentation

Become an expert in R — Interactive courses, Cheat Sheets, certificates and more!

witwit.coa

Internal Correspondence Analysis

Description

witwit.coa performs an Internal Correspondence Analysis. witwitsepan gives the computation and the barplot of the eigenvalues for each separated analysis in an Internal Correspondence Analysis.

Usage

witwit.coa(dudi, row.blocks, col.blocks, scannf = TRUE, nf = 2)
## S3 method for class 'witwit'
summary(object, ...)
witwitsepan(ww, mfrow = NULL, csub = 2, plot = TRUE)

Arguments

`dudi`	an object of class `coa`
`row.blocks`	a numeric vector indicating the row numbers for each block of rows
`col.blocks`	a numeric vector indicating the column numbers for each block of columns
`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

`object`	an object of class `witwit`
`...`	further arguments passed to or from other methods

`ww`	an object of class `witwit`
`mfrow`	a vector of the form "c(nr,nc)", otherwise computed by a special own function 'n2mfrow'
`csub`	a character size for the sub-titles, used with `par("cex")*csub`
`plot`	if FALSE, numeric results are returned

Value

returns a list of class witwit, coa and dudi (see as.dudi) containing

`rbvar`	a data frame with the within variances of the rows of the factorial coordinates
`lbw`	a data frame with the marginal weighting of the row classes
`cvar`	a data frame with the within variances of the columns of the factorial coordinates
`cbw`	a data frame with the marginal weighting of the column classes

Author(s)

Daniel Chessel Anne-Béatrice Dufour anne-beatrice.dufour@univ-lyon1.fr Correction by Campo Elías PARDO cepardot@cable.net.co

References

Cazes, P., Chessel, D. and Dolédec, S. (1988) L'analyse des correspondances internes d'un tableau partitionné : son usage en hydrobiologie. Revue de Statistique Appliquée, 36, 39–54.

Examples

data(ardeche)
coa1 <- dudi.coa(ardeche$tab, scann = FALSE, nf = 4)
ww <- witwit.coa(coa1, ardeche$row.blocks, ardeche$col.blocks, scann = FALSE)
ww
summary(ww)

if(adegraphicsLoaded()) {
  g1 <- s.class(ww$co, ardeche$sta.fac, plab.cex = 1.5, ellipseSi = 0, paxes.draw = FALSE, 
    plot = FALSE)
  g2 <- s.label(ww$co, plab.cex = 0.75, plot = FALSE)
  G <- superpose(g1, g2, plot = TRUE)
  
} else {
  s.class(ww$co, ardeche$sta.fac, clab = 1.5, cell = 0, axesell = FALSE)
  s.label(ww$co, add.p = TRUE, clab = 0.75)
}

witwitsepan(ww, c(4, 6))

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