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GPareto  

Gaussian Processes for Pareto Front Estimation and Optimization
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]
All associated links for this package
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 06 Nov. 2024.
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)
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