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brede_mat_nls_est

PURPOSE ^

brede_mat_nls_est - Non-negative least squares estimation

SYNOPSIS ^

function B = brede_mat_nls_est(X, Y, varargin)

DESCRIPTION ^

 brede_mat_nls_est    - Non-negative least squares estimation

       B = brede_mat_nls_est(X, Y, 'PropertyName', 'PropertyValue') )

       Input:    X     Independent variable as 'mat' structure or matrix 
                 Y     Dependent variable as 'mat' structure or matrix

       Property: Binit Starting guess for B regression parameters
                 Info  [ {0} | An integer ] Amount of debug information 

       Output:   B     Estimated parameters in 'mat' structure

       Non-negative least squares estimation. The model is:

         Y = X*B + U

       where U is Gaussian distributed and B is estimated to be
       non-negative.  

       Presently an estimation with iterations similar to non-negative
       matrix factorizations is implemented.

       Example:
         % A small Rasmus Bro example. First b should be 0.65 other two
         % parameters zero
         X = [ 73 71 52 ; 87 74 46 ; 72 2 7 ; 80 89 71 ];
         y = [ 49 67 68 20 ]';
         Bols = brede_mat_glm_est(X,y); Bols.matrix
         Bnls = brede_mat_nls_est(X,y); Bnls.matrix

       See also BREDE, BREDE_MAT, BREDE_MAT_GLM_EST, BREDE_MAT_NMF.

 $Id: brede_mat_nls_est.m,v 1.3 2008/06/05 18:17:16 fn Exp $

CROSS-REFERENCE INFORMATION ^

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