diff toolboxes/FullBNT-1.0.7/netlab3.3/gpcovar.m @ 0:e9a9cd732c1e tip

first hg version after svn

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/toolboxes/FullBNT-1.0.7/netlab3.3/gpcovar.m	Tue Feb 10 15:05:51 2015 +0000
@@ -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);
+