Calculate the prior covariance for the Sparse GP.
[covp, covf] = ogpcovarp(x1, x2)
[covp, covf] = ogpcovarp(net, x1, x2) considers the global OGP data
structure net and the two matrices x1, 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.
If called with a single input x1, the function returns only the
diagonal of ogpcovarp(x1,x1).
[covp, covf] = ogpcovarp(x1, x2) also returns the function
component of the covariance.
Relation between the function component and the value returned by
ogpcovarp is
covp = exp(net.bias) + covf
where covf is the covariance matrix returned by ogpcovarf and
bias is added to each kernel element.
For the available covariance functions see ogpcovarf.
The variable net is global: the kernel parameters and the bias value
are taken from this structure.
Copyright (c) Lehel Csató (2001-2004)