CPrunsFit: Candecomp/Parafac solutions
In ThreeWay: Three-Way Component Analysis

Description Usage Arguments Value Note Author(s) References See Also Examples

Computes all the Candecomp/Parafac solutions (CP) with r (from 1 to maxC) components.

1	CPrunsFit(X, n, m, p, maxC)

`X`	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
`maxC`	Maximum dimensionality for the `A`-mode

out

Matrix with columns: number of components for the A-mode, number of components for the B-mode, number of components for the C-mode, goodness of fit (%), total number of components

The structure of out is consistent with Tucker models. In CP, the first and forth columns are sufficient for choosing the optimal number of components.

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

H.A.L. Kiers (1991). Hierarchical relations among three-way methods. Psychometrika 56:449–470.

DimSelector, LineCon, CP

data(TV)
TVdata=TV[[1]]
# permutation of the modes so that the A-mode refers to students
TVdata <- permnew(TVdata, 16, 15, 30)
TVdata <- permnew(TVdata, 15, 30, 16)
# Fit values of CP with different numbers of components (from 1 to 5)
FitCP <- CPrunsFit(TVdata, 30, 16, 15, 5)