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author | Daniel Wolff |
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date | Fri, 19 Aug 2016 13:07:06 +0200 |
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function y = gauss(mu, covar, x) %GAUSS Evaluate a Gaussian distribution. % % Description % % Y = GAUSS(MU, COVAR, X) evaluates a multi-variate Gaussian density % in D-dimensions at a set of points given by the rows of the matrix X. % The Gaussian density has mean vector MU and covariance matrix COVAR. % % See also % GSAMP, DEMGAUSS % % Copyright (c) Ian T Nabney (1996-2001) [n, d] = size(x); [j, k] = size(covar); % Check that the covariance matrix is the correct dimension if ((j ~= d) | (k ~=d)) error('Dimension of the covariance matrix and data should match'); end invcov = inv(covar); mu = reshape(mu, 1, d); % Ensure that mu is a row vector x = x - ones(n, 1)*mu; fact = sum(((x*invcov).*x), 2); y = exp(-0.5*fact); y = y./sqrt((2*pi)^d*det(covar));