gpcovar

Purpose

Calculate the covariance for a Gaussian Process.

Synopsis 

cov = gpcovar(net, x)
[cov, covf] = gpcovar(net, x)

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.

Example

In the following example, the inverse covariance matrix is calculated for a set of training inputs x and is then passed to gpfwd so that predictions (with mean ytest and variance sigsq) can be made for the test inputs xtest. 

cninv = inv(gpcovar(net, x)); 
[ytest, sigsq] = gpfwd(net, xtest, cninv);

See Also

gp, gppak, gpunpak, gpcovarp, gpcovarf, gpfwd, gperr, gpgrad
Pages: Index

Copyright (c) Ian T Nabney (1996-9)