annotate toolboxes/FullBNT-1.0.7/netlab3.3/gauss.m @ 0:cc4b1211e677 tip

initial commit to HG from Changeset: 646 (e263d8a21543) added further path and more save "camirversion.m"
author Daniel Wolff
date Fri, 19 Aug 2016 13:07:06 +0200
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Daniel@0 1 function y = gauss(mu, covar, x)
Daniel@0 2 %GAUSS Evaluate a Gaussian distribution.
Daniel@0 3 %
Daniel@0 4 % Description
Daniel@0 5 %
Daniel@0 6 % Y = GAUSS(MU, COVAR, X) evaluates a multi-variate Gaussian density
Daniel@0 7 % in D-dimensions at a set of points given by the rows of the matrix X.
Daniel@0 8 % The Gaussian density has mean vector MU and covariance matrix COVAR.
Daniel@0 9 %
Daniel@0 10 % See also
Daniel@0 11 % GSAMP, DEMGAUSS
Daniel@0 12 %
Daniel@0 13
Daniel@0 14 % Copyright (c) Ian T Nabney (1996-2001)
Daniel@0 15
Daniel@0 16 [n, d] = size(x);
Daniel@0 17
Daniel@0 18 [j, k] = size(covar);
Daniel@0 19
Daniel@0 20 % Check that the covariance matrix is the correct dimension
Daniel@0 21 if ((j ~= d) | (k ~=d))
Daniel@0 22 error('Dimension of the covariance matrix and data should match');
Daniel@0 23 end
Daniel@0 24
Daniel@0 25 invcov = inv(covar);
Daniel@0 26 mu = reshape(mu, 1, d); % Ensure that mu is a row vector
Daniel@0 27
Daniel@0 28 x = x - ones(n, 1)*mu;
Daniel@0 29 fact = sum(((x*invcov).*x), 2);
Daniel@0 30
Daniel@0 31 y = exp(-0.5*fact);
Daniel@0 32
Daniel@0 33 y = y./sqrt((2*pi)^d*det(covar));