Constrainfit

Purpose

Finds A minimizing ||X-A*B'|| subject to constraints, given the small matrices (X ' B) and (B ' B)

Synopsis

[A]=constrainfit(XB,BtB,Aold);  % Unconstrained

opt = constrainfit('options');

opt.type='nonnegativity';

[A]=constrainfit(XB,BtB,Aold,opt); % Nonnegative

opt = constrainfit('options');

opt.type='columnwise';

opt.columnconstraints={0;2;0}; % If three columns

[A]=constrainfit(XB,BtB,Aold,opt); % Second column unimodal

Description

CONSTRAINTFIT solves the least squares problem behind bilinear, trilinear and other multilinear models. Assuming a model X = A*B ' and assuming that X and B are known, the least squares estimate of A is obtained. Rather than using X and B this algorithm uses the cross product matrices (X ' B) and (B ' B) which are generally smaller and less memory-demanding especially in multi-way models.

Inputs

• first = first input is this.

Optional Inputs

• second = optional second input is this.

Outputs

• firstout = first output is this.

Options

options = a structure array with the following fields:

• plots: [ {'none'} | 'final' ] governs plotting of results, and
• order: positive integer for polynomial order {default = 1}.

Example

>>This is an example
Error: does not exist

See Also

baselinew, deresolv