hetGP: Heteroskedastic Gaussian Process Modeling and Design under Replication

Performs Gaussian process regression with heteroskedastic noise following the model by Binois, M., Gramacy, R., Ludkovski, M. (2016) <arXiv:1611.05902>, 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.

Package details

AuthorMickael Binois, Robert B. Gramacy
MaintainerMickael Binois <mickael.binois@inria.fr>
LicenseLGPL
Version1.1.6
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("hetGP")

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hetGP documentation built on Oct. 3, 2023, 1:07 a.m.