Package: GPareto
Type: Package
Title: Gaussian Processes for Pareto Front Estimation and Optimization
Version: 1.2.0
Date: 2026-02-04
Authors@R: c(person(given = "Mickael",
                        family = "Binois",
                        role = c("aut", "cre"),
                        email = "mickael.binois@inria.fr",
                        comment = c(ORCID = "0000-0002-7225-1680")),
                 person(given = c("Victor"),
                        family = "Picheny",
                        role = "aut"))
Description: Gaussian process regression models, a.k.a. Kriging models,
        are applied to global multi-objective optimization of black-box
        functions. Multi-objective Expected Improvement and Step-wise
        Uncertainty Reduction sequential infill criteria are available.
        A quantification of uncertainty on Pareto fronts is provided
        using conditional simulations.
License: GPL-3
Depends: DiceKriging, moocore
Imports: Rcpp (>= 0.12.15), methods, rgenoud, pbivnorm, pso,
        randtoolbox, KrigInv, MASS, DiceDesign, ks, rgl
Suggests: knitr
VignetteBuilder: knitr
LinkingTo: Rcpp
URL: https://github.com/mbinois/GPareto
BugReports: https://github.com/mbinois/GPareto/issues
RoxygenNote: 7.3.3
Config/pak/sysreqs: cmake libfreetype6-dev libglu1-mesa-dev make
        texlive libpng-dev libuv1-dev libgl1-mesa-dev zlib1g-dev
Repository: https://mbinois.r-universe.dev
Date/Publication: 2026-02-08 21:42:48 UTC
RemoteUrl: https://github.com/mbinois/gpareto
RemoteRef: HEAD
RemoteSha: 51365eed6b11d4dc7241cc11b102191b01974d42
NeedsCompilation: yes
Packaged: 2026-06-24 10:13:24 UTC; root
Author: Mickael Binois [aut, cre] (ORCID:
    <https://orcid.org/0000-0002-7225-1680>),
  Victor Picheny [aut]
Maintainer: Mickael Binois <mickael.binois@inria.fr>