STATIS and Co-Inertia : Analysis of a series of paired ecological tables

Description

Prepares the analysis of a series of paired ecological tables. Partial Triadic Analysis (see pta) can be used thereafter to perform the analysis of this k-table.

Usage

ktab.match2ktabs(KTX, KTY)

Arguments

Value

a list of class ktab, subclass kcoinertia. See ktab

WARNING

IMPORTANT : KTX and KTY must have the same k-tables structure, the same number of columns, and the same column weights.

Author(s)

Jean Thioulouse ade4-jt@biomserv.univ-lyon1.fr

References

Thioulouse J., Simier M. and Chessel D. (2004). Simultaneous analysis of a sequence of paired ecological tables. Ecology 85, 272-283..

Simier, M., Blanc L., Pellegrin F., and Nandris D. (1999). Approche simultanée de K couples de tableaux : Application a l'étude des relations pathologie végétale - environnement. Revue de Statistique Appliquée, 47, 31-46.

Examples

data(meau)
wit1 <- withinpca(meau$mil, meau$plan$dat, scan = FALSE, scal = "total")
pcafau <- dudi.pca(meau$fau, scale = FALSE, scan = FALSE, nf = 2)
wit2 <- within(pcafau, meau$plan$dat, scan = FALSE, nf = 2)
kta1 <- ktab.within(wit1, colnames = rep(c("S1","S2","S3","S4","S5","S6"), 4))
kta2 <- ktab.within(wit2, colnames = rep(c("S1","S2","S3","S4","S5","S6"), 4))
kcoi <- ktab.match2ktabs(kta1, kta2)
ptacoi <- pta(kcoi, scan = FALSE, nf = 2)
plot(ptacoi)
kplot(ptacoi)

Worked out examples

> library(ade4)
> ### Name: ktab.match2ktabs
> ### Title: STATIS and Co-Inertia : Analysis of a series of paired
> ###   ecological tables
> ### Aliases: ktab.match2ktabs
> ### Keywords: multivariate
> 
> ### ** Examples
> 
> data(meau)
> wit1 <- withinpca(meau$mil, meau$plan$dat, scan = FALSE, scal = "total")
> pcafau <- dudi.pca(meau$fau, scale = FALSE, scan = FALSE, nf = 2)
> wit2 <- within(pcafau, meau$plan$dat, scan = FALSE, nf = 2)
> kta1 <- ktab.within(wit1, colnames = rep(c("S1","S2","S3","S4","S5","S6"), 4))
> kta2 <- ktab.within(wit2, colnames = rep(c("S1","S2","S3","S4","S5","S6"), 4))
> kcoi <- ktab.match2ktabs(kta1, kta2)
> ptacoi <- pta(kcoi, scan = FALSE, nf = 2)
> plot(ptacoi)

> kplot(ptacoi)

> 
> 
> 
>