CGP

Composite Gaussian Process Models

Fit composite Gaussian process (CGP) models as described in Ba and Joseph (2012) "Composite Gaussian Process Models for Emulating Expensive Functions", Annals of Applied Statistics. The CGP model is capable of approximating complex surfaces that are not second-order stationary. Important functions in this package are CGP, print.CGP, summary.CGP, predict.CGP and plotCGP.

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Description file content

Package
CGP
Type
Package
Title
Composite Gaussian Process Models
Version
2.1-1
Date
2018-06-11
Author
Shan Ba and V. Roshan Joseph
Maintainer
Shan Ba
Description
Fit composite Gaussian process (CGP) models as described in Ba and Joseph (2012) "Composite Gaussian Process Models for Emulating Expensive Functions", Annals of Applied Statistics. The CGP model is capable of approximating complex surfaces that are not second-order stationary. Important functions in this package are CGP, print.CGP, summary.CGP, predict.CGP and plotCGP.
License
LGPL-2.1
NeedsCompilation
no
Packaged
2018-06-12 14:20:18 UTC; ba.s
Repository
CRAN
Date/Publication
2018-06-12 15:08:19 UTC

install.packages('CGP')

2.1-1

4 months ago

Shan Ba

LGPL-2.1

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