CompModels: Pseudo Computer Models for Optimization

A suite of computer model test functions that can be used to test and evaluate algorithms for Bayesian (also known as sequential) optimization. Some of the functions have known functional forms, however, most are intended to serve as black-box functions where evaluation requires running computer code that reveals little about the functional forms of the objective and/or constraints. The primary goal of the package is to provide users (especially those who do not have access to real computer models) a source of reproducible and shareable examples that can be used for benchmarking algorithms. The package is a living repository, and so more functions will be added over time. For function suggestions, please do contact the author of the package.

Version: 0.2.0
Suggests: R.rsp, laGP
Published: 2020-11-03
Author: Tony Pourmohamad [aut, cre]
Maintainer: Tony Pourmohamad <tpourmohamad at gmail.com>
License: GPL-2
NeedsCompilation: yes
Materials: ChangeLog
CRAN checks: CompModels results

Documentation:

Reference manual: CompModels.pdf
Vignettes: An introduction to the CompModels package
CompModels: Diagrams of physics based computer models

Downloads:

Package source: CompModels_0.2.0.tar.gz
Windows binaries: r-devel: CompModels_0.2.0.zip, r-release: CompModels_0.2.0.zip, r-oldrel: CompModels_0.2.0.zip
macOS binaries: r-release (arm64): CompModels_0.2.0.tgz, r-oldrel (arm64): CompModels_0.2.0.tgz, r-release (x86_64): CompModels_0.2.0.tgz, r-oldrel (x86_64): CompModels_0.2.0.tgz
Old sources: CompModels archive

Linking:

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