predict.homGP {hetGP}

Gaussian process predictions using a homoskedastic noise GP object (of class homGP)

Description

Gaussian process predictions using a homoskedastic noise GP object (of class homGP)

Usage

## S3 method for class 'homGP'
predict(object, x, xprime = NULL, ...)

Arguments

object

an object of class homGP; e.g., as returned by mleHomGP

x

matrix of designs locations to predict at (one point per row)

xprime

optional second matrix of predictive locations to obtain the predictive covariance matrix between x and xprime

...

no other argument for this method

Details

The full predictive variance corresponds to the sum of sd2 and nugs. See mleHomGP for examples.

Value

list with elements

• mean: kriging mean;

• sd2: kriging variance (filtered, e.g. without the nugget value)

• cov: predictive covariance matrix between x and xprime

• nugs: nugget value at each prediction location, for consistency with mleHomGP.