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conda-forge/r-dfoptim

r-dfoptim

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Derivative-Free optimization algorithms. These algorithms do not require gradient information. More importantly, they can be used to solve non-smooth optimization problems.

Copied fromcf-post-staging / r-dfoptim

Installation

To install this package, run one of the following:

Conda
$conda install conda-forge::r-dfoptim

Usage Tracking

2023.1.0
2020.10_1
2018.2_1
2017.12_1
4 / 8 versions selected
Total downloads: 0

About

Summary

Derivative-Free optimization algorithms. These algorithms do not require gradient information. More importantly, they can be used to solve non-smooth optimization problems.

Information Last Updated

Sep 17, 2025 at 07:40

License

GPL-2.0-or-later

Total Downloads

86.0K

Platforms

noarch Version: 2023.1.0
Win 64 Version: 2017.12_1
Linux 64 Version: 2017.12_1
macOS 64 Version: 2017.12_1

Home

http://www.jhsph.edu/agingandhealth/People/Faculty_personal_pages/Varadhan.html