function [np] = expF_MLE(Y,distr)
%function [np] = expF_MLE(Y,distr)
%Maximum likelihood estimation with the given exponential family on data Y. See also 'expF_F.m'.
%
%INPUT:
% distr: 'normal'.
% Y : data, Y(:,t) is the t^{th} sample.
%OUTPUT:
% np: estimated natural parameters.
% distr = 'normal': np.t1 = C^{-1}*m, np.t2 = 1/2*C^{-1}, where m is the mean, C is the covariance matrix.
%Copyright (C) 2012-2014 Zoltan Szabo ("http://www.gatsby.ucl.ac.uk/~szabo/", "zoltan (dot) szabo (at) gatsby (dot) ucl (dot) ac (dot) uk")
%
%This file is part of the ITE (Information Theoretical Estimators) toolbox.
%
%ITE is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by
%the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
%
%This software is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of
%MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
%
%You should have received a copy of the GNU General Public License along with ITE. If not, see .
switch distr
case 'normal'
m = mean(Y,2);
C = cov(Y.');
invC = inv(C);
np.t1 = invC * m;
np.t2 = invC / 2;
otherwise
error('Distribution=?');
end