CRAN/E | hetGP

hetGP

Heteroskedastic Gaussian Process Modeling and Design under Replication

Installation

About

Performs Gaussian process regression with heteroskedastic noise following the model by Binois, M., Gramacy, R., Ludkovski, M. (2016) , with implementation details in Binois, M. & Gramacy, R. B. (2021) doi:10.18637/jss.v098.i13. The input dependent noise is modeled as another Gaussian process. Replicated observations are encouraged as they yield computational savings. Sequential design procedures based on the integrated mean square prediction error and lookahead heuristics are provided, and notably fast update functions when adding new observations.

Citation hetGP citation info

Key Metrics

Version 1.1.6
R ≥ 2.10
Published 2023-10-02 210 days ago
Needs compilation? yes
License LGPL-2
License LGPL-2.1
License LGPL-3
CRAN checks hetGP results

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Maintainer

Maintainer

Mickael Binois

mickael.binois@inria.fr

Authors

Mickael Binois
Robert B. Gramacy

Material

NEWS
Reference manual
Package source

Vignettes

a guide to the hetGP package

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

hetGP archive

Depends

R ≥ 2.10

Imports

Rcpp ≥ 0.12.3
MASS
methods
DiceDesign

Suggests

knitr
monomvn
lhs
colorspace

LinkingTo

Rcpp

Reverse Imports

activegp
quantkriging