www.pudn.com > gpml.rar > likelihoods.m, change:2007-06-26,size:1222b
% likelihood: likelihood functions are provided to be used by the binaryGP % function, for binary Gaussian process classification. Two likelihood % functions are provided: % % logistic % cumGauss % % The likelihood functions have three possible modes, the mode being selected % as follows (where "lik" stands for any likelihood function): % % (log) likelihood evaluation: [p, lp] = lik(y, f) % % where y are the targets, f the latent function values, p the probabilities % and lp the log probabilities. All vectors are the same size. % % derivatives (of the log): [lp, dlp, d2lp, d3lp] = lik(y, f, 'deriv') % % where lp is a number (sum of the log probablities for each case) and the % derivatives (up to order 3) of the logs wrt the latent values are vectors % (as the likelihood factorizes there are no mixed terms). % % moments wrt Gaussian measure: [m0, m1, m2] = lik(y, mu, var) % % where mk is the k'th moment: \int f^k lik(y,f) N(f|mu,var) df, and if y is % empty, it is assumed to be a vector of ones. % % See the help for the individual likelihood for the computations specific to % each likelihood function. % % Copyright (c) 2007 Carl Edward Rasmussen and Hannes Nickisch 2007-04-11.