## 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 B 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)
```