function net = glminit(net, prior)
%GLMINIT Initialise the weights in a generalized linear model.
% 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)
if ~strcmp(net.type, 'glm')
error('Model type should be ''glm'');
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);
error('prior must be a scalar or a structure');
net = glmunpak(net, w);