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function [e, edata, eprior, y, a] = glmerr(net, x, t)
%GLMERR Evaluate error function for generalized linear model.
%
% Description
% E = GLMERR(NET, X, T) takes a generalized linear model data
% structure NET together with a matrix X of input vectors and a matrix
% T of target vectors, and evaluates the error function E. The choice
% of error function corresponds to the output unit activation function.
% Each row of X corresponds to one input vector and each row of T
% corresponds to one target vector.
%
% [E, EDATA, EPRIOR, Y, A] = GLMERR(NET, X, T) also returns the data
% and prior components of the total error.
%
% [E, EDATA, EPRIOR, Y, A] = GLMERR(NET, X) also returns a matrix Y
% giving the outputs of the models and a matrix A giving the summed
% inputs to each output unit, where each row corresponds to one
% pattern.
%
% See also
% GLM, GLMPAK, GLMUNPAK, GLMFWD, GLMGRAD, GLMTRAIN
%
% Copyright (c) Ian T Nabney (1996-2001)
% Check arguments for consistency
errstring = consist(net, 'glm', x, t);
if ~isempty(errstring);
error(errstring);
end
[y, a] = glmfwd(net, x);
switch net.outfn
case 'linear' % Linear outputs
edata = 0.5*sum(sum((y - t).^2));
case 'logistic' % Logistic outputs
edata = - sum(sum(t.*log(y) + (1 - t).*log(1 - y)));
case 'softmax' % Softmax outputs
edata = - sum(sum(t.*log(y)));
otherwise
error(['Unknown activation function ', net.outfn]);
end
[e, edata, eprior] = errbayes(net, edata);
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