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CRAN: Package hetGP

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) <doi:10.48550/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.

Version: 1.1.8 Depends: R (≥ 2.10) Imports: Rcpp (≥ 0.12.3), MASS, methods, DiceDesign, mco, quadprog LinkingTo: Rcpp Suggests: knitr, monomvn, lhs, colorspace Published: 2025-05-08 DOI: 10.32614/CRAN.package.hetGP Author: Mickael Binois [aut, cre], Robert B. Gramacy [aut] Maintainer: Mickael Binois <mickael.binois at inria.fr> License: LGPL-2 | LGPL-2.1 | LGPL-3 [expanded from: LGPL] NeedsCompilation: yes Materials: NEWS CRAN checks: hetGP results Documentation: Downloads: Reverse dependencies: Linking:

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