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Diffstat (limited to 'sourcecodes/bnt-master/netlab3.3/gpcovar.m')
| -rw-r--r-- | sourcecodes/bnt-master/netlab3.3/gpcovar.m | 38 |
1 files changed, 38 insertions, 0 deletions
diff --git a/sourcecodes/bnt-master/netlab3.3/gpcovar.m b/sourcecodes/bnt-master/netlab3.3/gpcovar.m new file mode 100644 index 00000000..f71fa4db --- /dev/null +++ b/sourcecodes/bnt-master/netlab3.3/gpcovar.m @@ -0,0 +1,38 @@ +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); + |