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- function g=lcvplot(alpha,varargin)
- %
- % Computes and plots the Likelihood Cross-Validation score (LCV)
- % for local fits with different smoothing parameters.
- %
- % 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.
- k = size(alpha,1);
- z = zeros(k,4);
- for i=1:k
- z(i,:) = lcv(varargin{:},'alpha',alpha(i,:));
- end;
- plot(z(:,3),z(:,4));
- xlabel('Fitted DF');
- ylabel('LCV');
- g = [alpha z];
- return;
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