Package: hetGP
Type: Package
Title: Heteroskedastic Gaussian Process Modeling and Design under
        Replication
Version: 1.1.9
Date: 2026-04-17
Authors@R: c(person(given = "Mickael",
                        family = "Binois",
                        role = c("aut", "cre"),
                        email = "mickael.binois@inria.fr"),
                 person(given = c("Robert", "B."),
                        family = "Gramacy",
                        role = "aut"))
Description: 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.
License: LGPL
LazyData: FALSE
Depends: R (>= 2.10),
Imports: Rcpp (>= 0.12.3), MASS, methods, DiceDesign, mco, quadprog
LinkingTo: Rcpp
Suggests: knitr, monomvn, lhs, colorspace
VignetteBuilder: knitr
RoxygenNote: 7.3.3
NeedsCompilation: yes
Packaged: 2026-06-22 10:42:33 UTC; root
Author: Mickael Binois [aut, cre], Robert B. Gramacy [aut]
Maintainer: Mickael Binois <mickael.binois@inria.fr>
Repository: https://mbinois.r-universe.dev
Date/Publication: 2026-04-23 17:52:07 UTC
RemoteUrl: https://github.com/cran/hetGP
RemoteRef: HEAD
RemoteSha: 6df210a8bdfccc52e795d418fd0f7f9f497a8ae7