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OOR  

Optimistic Optimization in R
View on CRAN: Click here


Download and install OOR package within the R console
Install from CRAN:
install.packages("OOR")

Install from Github:
library("remotes")
install_github("cran/OOR")

Install by package version:
library("remotes")
install_version("OOR", "0.1.4")



Attach the package and use:
library("OOR")
Maintained by
M. Binois
[Scholar Profile | Author Map]
First Published: 2017-02-03
Latest Update: 2023-08-23
Description:
Implementation of optimistic optimization methods for global optimization of deterministic or stochastic functions. The algorithms feature guarantees of the convergence to a global optimum. They require minimal assumptions on the (only local) smoothness, where the smoothness parameter does not need to be known. They are expected to be useful for the most difficult functions when we have no information on smoothness and the gradients are unknown or do not exist. Due to the weak assumptions, however, they can be mostly effective only in small dimensions, for example, for hyperparameter tuning.
How to cite:
M. Binois (2017). OOR: Optimistic Optimization in R. R package version 0.1.4, https://cran.r-project.org/web/packages/OOR. Accessed 29 Mar. 2025.
Previous versions and publish date:
0.1.1 (2017-02-03 14:32), 0.1.2 (2018-02-01 00:31), 0.1.3 (2020-03-23 12:30)
Other packages that cited OOR R package
View OOR citation profile
Other R packages that OOR depends, imports, suggests or enhances
Complete documentation for OOR
Functions, R codes and Examples using the OOR R package
Some associated functions: OOR . POO . StoSOO . Testfunctions . 
Some associated R codes: POO.R . RSOO-package.R . StoSOO.R . Testfunctions.R .  Full OOR package functions and examples
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