Mercurial > hg > camir-aes2014
annotate 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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rev | line source |
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wolffd@0 | 1 function [cov, covf] = gpcovar(net, x) |
wolffd@0 | 2 %GPCOVAR Calculate the covariance for a Gaussian Process. |
wolffd@0 | 3 % |
wolffd@0 | 4 % Description |
wolffd@0 | 5 % |
wolffd@0 | 6 % COV = GPCOVAR(NET, X) takes a Gaussian Process data structure NET |
wolffd@0 | 7 % together with a matrix X of input vectors, and computes the |
wolffd@0 | 8 % covariance matrix COV. The inverse of this matrix is used when |
wolffd@0 | 9 % calculating the mean and variance of the predictions made by NET. |
wolffd@0 | 10 % |
wolffd@0 | 11 % [COV, COVF] = GPCOVAR(NET, X) also generates the covariance matrix |
wolffd@0 | 12 % due to the covariance function specified by NET.COVARFN as calculated |
wolffd@0 | 13 % by GPCOVARF. |
wolffd@0 | 14 % |
wolffd@0 | 15 % See also |
wolffd@0 | 16 % GP, GPPAK, GPUNPAK, GPCOVARP, GPCOVARF, GPFWD, GPERR, GPGRAD |
wolffd@0 | 17 % |
wolffd@0 | 18 |
wolffd@0 | 19 % Copyright (c) Ian T Nabney (1996-2001) |
wolffd@0 | 20 |
wolffd@0 | 21 % Check arguments for consistency |
wolffd@0 | 22 errstring = consist(net, 'gp', x); |
wolffd@0 | 23 if ~isempty(errstring); |
wolffd@0 | 24 error(errstring); |
wolffd@0 | 25 end |
wolffd@0 | 26 |
wolffd@0 | 27 ndata = size(x, 1); |
wolffd@0 | 28 |
wolffd@0 | 29 % Compute prior covariance |
wolffd@0 | 30 if nargout >= 2 |
wolffd@0 | 31 [covp, covf] = gpcovarp(net, x, x); |
wolffd@0 | 32 else |
wolffd@0 | 33 covp = gpcovarp(net, x, x); |
wolffd@0 | 34 end |
wolffd@0 | 35 |
wolffd@0 | 36 % Add output noise variance |
wolffd@0 | 37 cov = covp + (net.min_noise + exp(net.noise))*eye(ndata); |
wolffd@0 | 38 |