ade4: kdist2ktab – R documentation

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kdist2ktab

Transformation of K distance matrices (object 'kdist') into K Euclidean representations (object 'ktab')

Description

The function creates a ktab object with the Euclidean representations from a kdist object. Notice that the euclid attribute must be TRUE for all elements.

Usage

kdist2ktab(kd, scale = TRUE, tol = 1e-07)

Arguments

`kd`	an object of class `kdist`
`scale`	a logical value indicating whether the inertia of Euclidean representations are equal to 1 (TRUE) or not (FALSE).
`tol`	a tolerance threshold, an eigenvalue is considered equal to zero if `eig$values` > (`eig$values[1` * tol)

Value

returns a list of class ktab containing for each distance of kd the data frame of its Euclidean representation

Author(s)

Daniel Chessel
Anne-Béatrice Dufour anne-beatrice.dufour@univ-lyon1.fr

Examples

data(friday87)
fri.w <- ktab.data.frame(friday87$fau, friday87$fau.blo, tabnames = friday87$tab.names)
fri.kd <- lapply(1:10, function(x) dist.binary(fri.w[[x]], 10))
names(fri.kd) <- substr(friday87$tab.names, 1, 4)
fri.kd <- kdist(fri.kd)
fri.ktab <- kdist2ktab(kd = fri.kd)
fri.sepan <- sepan(fri.ktab)
plot(fri.sepan)

tapply(fri.sepan$Eig, fri.sepan$TC[,1], sum)
# the sum of the eigenvalues is constant and equal to 1, for each K tables

fri.statis <- statis(fri.ktab, scan = FALSE, nf = 2)
round(fri.statis$RV, dig = 2)

fri.mfa <- mfa(fri.ktab, scan = FALSE, nf = 2)
fri.mcoa <- mcoa(fri.ktab, scan = FALSE, nf = 2)

apply(fri.statis$RV, 1, mean) 
fri.statis$RV.tabw 
plot(apply(fri.statis$RV, 1, mean), fri.statis$RV.tabw)
plot(fri.statis$RV.tabw, fri.statis$RV.tabw)

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