predict.hetGP {hetGP} | R Documentation |
Gaussian process predictions using a heterogeneous noise GP object (of class hetGP
)
Description
Gaussian process predictions using a heterogeneous noise GP object (of class hetGP
)
Usage
## S3 method for class 'hetGP'
predict(object, x, noise.var = FALSE, xprime = NULL, nugs.only = FALSE, ...)
Arguments
object |
an object of class |
x |
matrix of designs locations to predict at (one point per row) |
noise.var |
should the variance of the latent variance process be returned? |
xprime |
optional second matrix of predictive locations to obtain the predictive covariance matrix between |
nugs.only |
if |
... |
no other argument for this method. |
Details
The full predictive variance corresponds to the sum of sd2
and nugs
.
See mleHetGP
for examples.
Value
list with elements
-
mean
: kriging mean; -
sd2
: kriging variance (filtered, e.g. without the nugget values) -
nugs
: noise variance prediction -
sd2_var
: (returned ifnoise.var = TRUE
) kriging variance of the noise process (i.e., on log-variances iflogN = TRUE
) -
cov
: (returned ifxprime
is given) predictive covariance matrix betweenx
andxprime