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hetGP  

Heteroskedastic Gaussian Process Modeling and Design under Replication
View on CRAN: Click here


Download and install hetGP package within the R console
Install from CRAN:
install.packages("hetGP")

Install from Github:
library("remotes")
install_github("cran/hetGP")

Install by package version:
library("remotes")
install_version("hetGP", "1.1.8")



Attach the package and use:
library("hetGP")
Maintained by
Mickael Binois
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-09-28
Latest Update: 2025-05-08
Description:
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) . 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.
How to cite:
Mickael Binois (2017). hetGP: Heteroskedastic Gaussian Process Modeling and Design under Replication. R package version 1.1.8, https://cran.r-project.org/web/packages/hetGP. Accessed 15 Jul. 2026.
Previous versions and publish date:
(2026-07-09 07:47), 1.0.0 (2017-09-28 16:46), 1.0.1 (2017-11-29 15:48), 1.0.2 (2018-02-06 23:49), 1.1.0 (2018-09-18 21:20), 1.1.1 (2019-01-10 15:00), 1.1.2 (2019-10-24 10:30), 1.1.3 (2021-03-17 07:50), 1.1.4 (2021-07-08 11:10), 1.1.5 (2023-03-08 10:40), 1.1.6 (2023-10-02 23:40), 1.1.7 (2024-09-04 15:40), 1.1.8 (2025-05-08 13:40)
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Complete documentation for hetGP
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