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function net = glminit(net, prior)
%GLMINIT Initialise the weights in a generalized linear model.
%
% Description
%
% NET = GLMINIT(NET, PRIOR) takes a generalized linear model NET and
% sets the weights and biases by sampling from a Gaussian distribution.
% If PRIOR is a scalar, then all of the parameters (weights and biases)
% are sampled from a single isotropic Gaussian with inverse variance
% equal to PRIOR. If PRIOR is a data structure similar to that in
% MLPPRIOR but for a single layer of weights, then the parameters are
% sampled from multiple Gaussians according to their groupings (defined
% by the INDEX field) with corresponding variances (defined by the
% ALPHA field).
%
% See also
% GLM, GLMPAK, GLMUNPAK, MLPINIT, MLPPRIOR
%
% Copyright (c) Ian T Nabney (1996-2001)
errstring = consist(net, 'glm');
if ~isempty(errstring);
error(errstring);
end
if isstruct(prior)
sig = 1./sqrt(prior.index*prior.alpha);
w = sig'.*randn(1, net.nwts);
elseif size(prior) == [1 1]
w = randn(1, net.nwts).*sqrt(1/prior);
else
error('prior must be a scalar or a structure');
end
net = glmunpak(net, w);
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