dfoptim
Derivative-Free Optimization
Derivative-Free optimization algorithms. These algorithms do not require gradient information. More importantly, they can be used to solve non-smooth optimization problems.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
2023.1.0 |
rolling linux/jammy R-4.5 | dfoptim_2023.1.0.tar.gz |
72.2 KiB |
2023.1.0 |
rolling linux/noble R-4.5 | dfoptim_2023.1.0.tar.gz |
72.1 KiB |
2023.1.0 |
rolling source/ R- | dfoptim_2023.1.0.tar.gz |
14.3 KiB |
2023.1.0 |
latest linux/jammy R-4.5 | dfoptim_2023.1.0.tar.gz |
72.2 KiB |
2023.1.0 |
latest linux/noble R-4.5 | dfoptim_2023.1.0.tar.gz |
72.1 KiB |
2023.1.0 |
latest source/ R- | dfoptim_2023.1.0.tar.gz |
14.3 KiB |
2023.1.0 |
2026-04-26 source/ R- | dfoptim_2023.1.0.tar.gz |
14.3 KiB |
2023.1.0 |
2026-04-23 source/ R- | dfoptim_2023.1.0.tar.gz |
14.3 KiB |
2023.1.0 |
2026-04-09 windows/windows R-4.5 | dfoptim_2023.1.0.zip |
74.7 KiB |
2023.1.0 |
2025-04-20 source/ R- | dfoptim_2023.1.0.tar.gz |
14.3 KiB |