genproc

A list of original configuration matrices

configs

The maximum number of iterations allowed

maxit

The relative error tolerance for determining numeric convergence.

reltol

Logical indicating whether or not to use random starts (only applicable when the
dimensionality is two).

random

This function finds K orthogonal rotation matrices so that the rotated versions of the input 
configurations match each other optimally in the least-squares sense. The algorithm depends on the
starting values for the rotation matrices. At present identity matrices are used as starting values.
Only rotations / reflections are considered -- no scaling or translation factors are included.

Functions for performing least-squares bilinear clustering of
three-way data. The method uses the bilinear decomposition (or bi-additive
model) to model two-way matrix slices while clustering over the third way.
Up to four different types of clusters are included, one for each term of the
bilinear decomposition. In this way, matrices are clustered simultaneously on
(a subset of) their overall means, row margins, column margins and row-column
interactions. The orthogonality of the bilinear model results in separability of
the joint clustering problem into four separate ones. Three of these sub-problems
are specific k-means problems, while a special algorithm is implemented for the
interactions. Plotting methods are provided, including biplots for the low-rank
approximations of the interactions.

genproc: Generalized Procrustes Rotation

Description

Usage

Arguments

References