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)