Home > chronux_1_15 > locfit > lcvplot.m

lcvplot

PURPOSE ^

Computes and plots the Likelihood Cross-Validation score (LCV)

SYNOPSIS ^

function g=lcvplot(alpha,varargin)

DESCRIPTION ^

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

 Usage:  g=lcvplot(alpha,varargin)


 The first argument to lcvplot(), 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 lcv() (and locfit()). The results
 are stored in a matrix, and LCV score ploted against the degrees of
 freedom.

CROSS-REFERENCE INFORMATION ^

This function calls: This function is called by:

SOURCE CODE ^

0001 function g=lcvplot(alpha,varargin)
0002 % Computes and plots the Likelihood Cross-Validation score (LCV)
0003 % for local fits with different smoothing parameters.
0004 %
0005 % Usage:  g=lcvplot(alpha,varargin)
0006 %
0007 %
0008 % The first argument to lcvplot(), alpha, should be a matrix with one
0009 % or two columns (first column = nearest neighbor component, second
0010 % column = constant component). Each row of this matrix is, in turn,
0011 % passed as the 'alpha' argument to lcv() (and locfit()). The results
0012 % are stored in a matrix, and LCV score ploted against the degrees of
0013 % freedom.
0014 
0015 k = size(alpha,1);
0016 z = zeros(k,4);
0017 
0018 for i=1:k
0019   z(i,:) = lcv(varargin{:},'alpha',alpha(i,:));
0020 end;
0021 
0022 plot(z(:,3),z(:,4));
0023 xlabel('Fitted DF');
0024 ylabel('LCV');
0025 
0026 g = [alpha z];
0027 return;

Generated on Tue 15-Aug-2006 22:51:57 by m2html © 2003