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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

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