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view toolboxes/FullBNT-1.0.7/KPMstats/gaussian_prob.m @ 0:cc4b1211e677 tip
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646 (e263d8a21543) added further path and more save "camirversion.m"
author | Daniel Wolff |
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date | Fri, 19 Aug 2016 13:07:06 +0200 |
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function p = gaussian_prob(x, m, C, use_log) % GAUSSIAN_PROB Evaluate a multivariate Gaussian density. % p = gaussian_prob(X, m, C) % p(i) = N(X(:,i), m, C) where C = covariance matrix and each COLUMN of x is a datavector % p = gaussian_prob(X, m, C, 1) returns log N(X(:,i), m, C) (to prevents underflow). % % If X has size dxN, then p has size Nx1, where N = number of examples if nargin < 4, use_log = 0; end if length(m)==1 % scalar x = x(:)'; end [d N] = size(x); %assert(length(m)==d); % slow m = m(:); M = m*ones(1,N); % replicate the mean across columns denom = (2*pi)^(d/2)*sqrt(abs(det(C))); mahal = sum(((x-M)'*inv(C)).*(x-M)',2); % Chris Bregler's trick if any(mahal<0) warning('mahal < 0 => C is not psd') end if use_log p = -0.5*mahal - log(denom); else p = exp(-0.5*mahal) / (denom+eps); end