# CPfitpartitioning: Fit of each entity per mode In ThreeWay: Three-Way Component Analysis

## Description

Computation of fit contributions.

## Usage

 `1` ``` CPfitpartitioning(Xprep, n, m, p, A, B, C, laba, labb, labc) ```

## Arguments

 `Xprep` Matrix (or data.frame coerced to a matrix) of order (`n` `x` `mp`) containing the matricized array (frontal slices) `n` Number of `A`-mode entities `m` Number of `B`-mode entities `p` Number of `C`-mode entities `A` Component matrix for the `A`-mode `B` Component matrix for the `B`-mode `C` Component matrix for the `C`-mode `laba` Optional vector of length `n` containing the labels of the `A`-mode entities `labb` Optional vector of length `m` containing the labels of the `B`-mode entities `labc` Optional vector of length `p` containing the labels of the `C`-mode entities

## Value

A list including the following components:

 `fitA` Fit contribution for the `A`-mode entities `fitB` Fit contribution for the `B`-mode entities `fitC` Fit contribution for the `C`-mode entities

## Author(s)

Maria Antonietta Del Ferraro mariaantonietta.delferraro@yahoo.it
Henk A.L. Kiers h.a.l.kiers@rug.nl
Paolo Giordani paolo.giordani@uniroma1.it

`CP`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15``` ```data(TV) TVdata=TV[[1]] labSCALE=TV[[2]] labPROGRAM=TV[[3]] labSTUDENT=TV[[4]] # permutation of the modes so that the A-mode refers to students TVdata <- permnew(TVdata, 16, 15, 30) TVdata <- permnew(TVdata, 15, 30, 16) # CP solution TVcp <- CPfuncrep(TVdata, 30, 16, 15, 2, 1, 1, 1, 0, 1e-6, 10000) # Fitpartitioning of the CP solution FitCP <- CPfitpartitioning(TVdata, 30, 16, 15, TVcp\$A, TVcp\$B, TVcp\$C, labSTUDENT, labSCALE, labPROGRAM) # Fitpartitioning of the CP solution (when labels are not available) FitCP <- CPfitpartitioning(TVdata, 30, 16, 15, TVcp\$A, TVcp\$B, TVcp\$C) ```