Mercurial > hg > camir-aes2014
view toolboxes/FullBNT-1.0.7/netlab3.3/gpcovar.m @ 0:e9a9cd732c1e tip
first hg version after svn
author | wolffd |
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date | Tue, 10 Feb 2015 15:05:51 +0000 |
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function [cov, covf] = gpcovar(net, x) %GPCOVAR Calculate the covariance for a Gaussian Process. % % Description % % COV = GPCOVAR(NET, X) takes a Gaussian Process data structure NET % together with a matrix X of input vectors, and computes the % covariance matrix COV. The inverse of this matrix is used when % calculating the mean and variance of the predictions made by NET. % % [COV, COVF] = GPCOVAR(NET, X) also generates the covariance matrix % due to the covariance function specified by NET.COVARFN as calculated % by GPCOVARF. % % See also % GP, GPPAK, GPUNPAK, GPCOVARP, GPCOVARF, GPFWD, GPERR, GPGRAD % % Copyright (c) Ian T Nabney (1996-2001) % Check arguments for consistency errstring = consist(net, 'gp', x); if ~isempty(errstring); error(errstring); end ndata = size(x, 1); % Compute prior covariance if nargout >= 2 [covp, covf] = gpcovarp(net, x, x); else covp = gpcovarp(net, x, x); end % Add output noise variance cov = covp + (net.min_noise + exp(net.noise))*eye(ndata);