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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 [covp, covf] = gpcovarp(net, x1, x2) %GPCOVARP Calculate the prior covariance for a Gaussian Process. % % Description % % COVP = GPCOVARP(NET, X1, X2) takes a Gaussian Process data structure % NET together with two matrices X1 and X2 of input vectors, and % computes the matrix of the prior covariance. This is the function % component of the covariance plus the exponential of the bias term. % % [COVP, COVF] = GPCOVARP(NET, X1, X2) also returns the function % component of the covariance. % % See also % GP, GPCOVAR, GPCOVARF, GPERR, GPGRAD % % Copyright (c) Ian T Nabney (1996-2001) errstring = consist(net, 'gp', x1); if ~isempty(errstring); error(errstring); end if size(x1, 2) ~= size(x2, 2) error('Number of variables in x1 and x2 must be the same'); end covf = gpcovarf(net, x1, x2); covp = covf + exp(net.bias);