# gcvplot

## PURPOSE

## SYNOPSIS

function g=gcvplot(alpha,varargin)

## DESCRIPTION

     Computes and plots the Generalized Cross-Validation score (GCV)
     for local fits with different smoothing parameters.

     The first argument to gcvplot(), alpha, should be a matrix with one
     or two columns (first column = nearest neighbor component, second
     column = constant component). Each row of this matrix is, in turn,
     passed as the 'alpha' argument to gcv() (and locfit()). The results
     are stored in a matrix, and GCV score ploted against the degrees of
     freedom.

## CROSS-REFERENCE INFORMATION

This function calls:

- gcv

This function is called by:

- fig2_7 Local Regression and Likelihood, Figure 2.7.

## SOURCE CODE

    0001 function g=gcvplot(alpha,varargin)
    0002 %
    0003 % Computes and plots the Generalized Cross-Validation score (GCV)
    0004 % for local fits with different smoothing parameters.
    0005 %
    0006 % The first argument to gcvplot(), alpha, should be a matrix with one
    0007 % or two columns (first column = nearest neighbor component, second
    0008 % column = constant component). Each row of this matrix is, in turn,
    0009 % passed as the 'alpha' argument to gcv() (and locfit()). The results
    0010 % are stored in a matrix, and GCV score ploted against the degrees of
    0011 % freedom.
    0012
    0013 k = size(alpha,1);
    0014 z = zeros(k,4);
    0015
    0016 for i=1:k
    0017   z(i,:) = gcv(varargin{:},'alpha',alpha(i,:));
    0018 end;
    0019
    0020 plot(z(:,3),z(:,4));
    0021 xlabel('Fitted DF');
    0022 ylabel('GCV');
    0023
    0024 g = [alpha z];
    0025 return;