Package: GPareto 1.2.0

GPareto: Gaussian Processes for Pareto Front Estimation and Optimization

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.

Authors:Mickael Binois [aut, cre], Victor Picheny [aut]

GPareto_1.2.0.tar.gz
GPareto_1.2.0.zip(r-4.7)GPareto_1.2.0.zip(r-4.6)GPareto_1.2.0.zip(r-4.5)
GPareto_1.2.0.tgz(r-4.6-x86_64)GPareto_1.2.0.tgz(r-4.6-arm64)GPareto_1.2.0.tgz(r-4.5-x86_64)GPareto_1.2.0.tgz(r-4.5-arm64)
GPareto_1.2.0.tar.gz(r-4.7-arm64)GPareto_1.2.0.tar.gz(r-4.7-x86_64)GPareto_1.2.0.tar.gz(r-4.6-arm64)GPareto_1.2.0.tar.gz(r-4.6-x86_64)
GPareto_1.2.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
GPareto/json (API)

# Install 'GPareto' in R:

install.packages('GPareto', repos = c('https://mbinois.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/mbinois/gpareto/issues

Uses libs:

c++– GNU Standard C++ Library v3

On CRAN:

cpp

7.08 score 18 stars 1 packages 43 scripts 3.4k downloads 36 exports 56 dependencies

Last updated from:51365eed6b. Checks:13 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	OK	212
linux-devel-x86_64	OK	216
source / vignettes	OK	478
linux-release-arm64	OK	209
linux-release-x86_64	OK	208
macos-release-arm64	OK	106
macos-release-x86_64	OK	353
macos-oldrel-arm64	OK	115
macos-oldrel-x86_64	OK	367
windows-devel	OK	173
windows-release	OK	180
windows-oldrel	OK	173
wasm-release	OK	191

Exports:checkPredict CPF crit_EHI crit_EMI crit_optimizer crit_qEHI crit_SMS crit_SUR DTLZ1 DTLZ2 DTLZ3 DTLZ7 easyGParetoptim fastfun getDesign GParetoptim integration_design_optim MOP2 MOP3 nonDomSet OKA1 P1 P2 ParetoSetDensity plot_uncertainty plotGPareto plotParetoEmp plotParetoGrid plotSymDevFun plotSymDifRNP predict_kms ZDT1 ZDT2 ZDT3 ZDT4 ZDT6

Dependencies:anMC base64enc bslib cachem cli DiceDesign DiceKriging digest evaluate fastmap FNN fontawesome fs highr htmltools htmlwidgets jquerylib jsonlite kernlab KernSmooth knitr KrigInv ks lattice lifecycle magrittr MASS Matrix matrixStats mclust memoise mgcv mime moocore multicool mvtnorm nlme pbivnorm pracma pso R6 randtoolbox rappdirs rbibutils Rcpp RcppArmadillo Rdpack rgenoud rgl rlang rmarkdown rngWELL sass tinytex xfun yaml

a guide to the GPareto package

Introduction | Method | Package overview and options | Illustrating examples using GPareto

Rendered fromGPareto_vignette.Rnwusingknitr::knitr

Last update: 2026-02-08
Started: 2018-02-04

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Package GPareto	GPareto-package GPareto
Prevention of numerical instability for a new observation	checkPredict
Conditional Pareto Front simulations	CPF
Expected Hypervolume Improvement with m objectives	crit_EHI
Expected Maximin Improvement with m objectives	crit_EMI
Maximization of multiobjective infill criterion	crit_optimizer
Batch Expected Hypervolume Improvement with m objectives	crit_qEHI
Analytical expression of the SMS-EGO criterion with m>1 objectives	crit_SMS
Analytical expression of the SUR criterion for two or three objectives.	crit_SUR
EGO algorithm for multiobjective optimization	easyGParetoptim
Fast-to-evaluate function wrapper	fastfun
Get design corresponding to an objective target	getDesign
Sequential multi-objective Expected Improvement maximization and model re-estimation, with a number of iterations fixed in advance by the user	GParetoptim
Function to build integration points (for the SUR criterion)	integration_design_optim
Non-dominated points with respect to a reference	nonDomSet
Estimation of Pareto set density	ParetoSetDensity
Plot uncertainty	plot_uncertainty
Plot multi-objective optimization results and post-processing	plotGPareto
Pareto front visualization	plotParetoEmp
Visualisation of Pareto front and set	plotParetoGrid
Display the Symmetric Deviation Function	plotSymDevFun
Symmetrical difference of RNP sets	plotSymDifRNP
Predict function for list of 'km' models.	predict_kms
Test functions of x	DTLZ1 DTLZ2 DTLZ3 DTLZ7 MOP2 MOP3 OKA1 P1 P2 ZDT1 ZDT2 ZDT3 ZDT4 ZDT6