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GPareto
View on CRAN: Click
here
Download and install GPareto package within the R console
Install from CRAN:
install.packages("GPareto")
Install from Github:
library("remotes")
install_github("cran/GPareto")
Install by package version:
library("remotes")
install_version("GPareto", "1.1.8")
Attach the package and use:
library("GPareto")
Maintained by
Mickael Binois
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.GPareto . https://github.com/mbinois/GPareto/issues . https://github.com/mbinois/GPareto . GPareto citation info . GPareto results . GPareto.pdf . a guide to the GPareto package . GPareto_1.1.8.tar.gz . GPareto_1.1.8.zip . GPareto_1.1.8.zip . GPareto_1.1.8.zip . GPareto_1.1.8.tgz . GPareto_1.1.8.tgz . GPareto_1.1.8.tgz . GPareto_1.1.8.tgz . GPareto archive . https://CRAN.R-project.org/package=GPareto .
First Published: 2014-12-17
Latest Update: 2024-01-26
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.
How to cite:
Mickael Binois (2014). GPareto: Gaussian Processes for Pareto Front Estimation and Optimization. R package version 1.1.8, https://cran.r-project.org/web/packages/GPareto. Accessed 09 May. 2025.
Previous versions and publish date:
1.0.0 (2014-12-17 13:08), 1.0.1 (2015-07-03 12:50), 1.0.2 (2016-03-02 02:13), 1.0.3 (2016-11-11 17:36), 1.1.0 (2017-06-29 07:30), 1.1.1 (2018-02-01 00:26), 1.1.2 (2018-12-10 11:10), 1.1.3 (2019-05-09 22:30), 1.1.4.1 (2020-04-01 13:25), 1.1.4 (2019-12-06 16:50), 1.1.6 (2021-05-31 11:50), 1.1.7 (2022-06-24 14:20)
Other packages that cited GPareto R package
View GPareto citation profile
Other R packages that GPareto depends,
imports, suggests or enhances
Complete documentation for GPareto
Functions, R codes and Examples using
the GPareto R package
Some associated functions: CPF . GPareto-package . GParetoptim . ParetoSetDensity . TestFunctions . checkPredict . crit_EHI . crit_EMI . crit_SMS . crit_SUR . crit_optimizer . crit_qEHI . easyGParetoptim . fastfun-class . fastfun . getDesign . integration_design_optim . nonDomSet . plotGPareto . plotParetoEmp . plotParetoGrid . plotSymDevFun . plotSymDifRNP . plot_uncertainty . predict_kms .
Some associated R codes: CPF.R . EEV.2D.computation.R . EHI_2d.R . EMI_2d.R . GPareto-package.R . GParetoptim.R . ParetoSetDensity.R . RcppExports.R . SAA_MEI.R . TestFunctions.R . checkPredict.R . computeQuickKrigcov2.R . crit_EHI.R . crit_EMI.R . crit_SMS.R . crit_SUR.R . crit_optimizer.R . easyGParetoptim.R . fastfun.R . getDesign.R . integration_design_optim.R . plotGPareto.R . plotParetoEmp.R . plotParetoGrid.R . plotSymDevFun.R . plotSymDifRNP.R . plot_uncertainty.R . predictkms.R . prob.of.non.domination.R . Full GPareto package functions and examples
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