wolffd@0: wolffd@0:
wolffd@0:wolffd@0: covp = gpcovarp(net, x1, x2) wolffd@0: [covp, covf] = gpcovarp(net, x1, x2) wolffd@0:wolffd@0: wolffd@0: wolffd@0:
covp = gpcovarp(net, x1, x2)
takes
wolffd@0: a Gaussian Process data structure net
together with
wolffd@0: two matrices x1
and x2
of input vectors,
wolffd@0: and computes the matrix of the prior covariance. This is
wolffd@0: the function component of the covariance plus the exponential of the bias
wolffd@0: term.
wolffd@0:
wolffd@0:
[covp, covf] = gpcovarp(net, x1, x2)
also returns the function
wolffd@0: component of the covariance.
wolffd@0:
wolffd@0:
gp
, gpcovar
, gpcovarf
, gperr
, gpgrad
Copyright (c) Ian T Nabney (1996-9) wolffd@0: wolffd@0: wolffd@0: wolffd@0: