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brede_mat_pcr_est

PURPOSE ^

brede_mat_pcr_est - Principal component regression estimation

SYNOPSIS ^

function B = brede_mat_pcr_est(X, Y, varargin)

DESCRIPTION ^

 brede_mat_pcr_est    - Principal component regression estimation

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

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

       Property: Components  [ An integer ] Number of principal
                       components used.
                 Info  [ {0} | An integer ] Amount of debug information 

       Output:   B     Estimated parameters in 'mat' structure

       Principal component regression estimation. The model is:

         Y = X*B + U

       where U is Gaussian distributed and B is estimated based on a
       principal component analysis of X.

       Presently only the highest variance principal components are
       used in the regression. If the number of components are not given
       then it is set by a rule of thumb as the square root of half the
       minimum of the dimension of either X or Y.
  
       See also BREDE, BREDE_MAT, BREDE_MAT_GLM_EST, BREDE_MAT_NLS_EST,
                BREDE_MAT_NMF.

 $Id: brede_mat_pcr_est.m,v 1.1 2008/04/16 22:21:22 fn Exp $

CROSS-REFERENCE INFORMATION ^

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