kdist2ktab {ade4} | R Documentation

## 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 chessel@biomserv.univ-lyon1.fr
Anne B Dufour dufour@biomserv.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, csub = 3)

    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)

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