dfoptim (2018.2-1)

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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.

Maintainer: Ravi Varadhan
Author(s): Ravi Varadhan, Johns Hopkins University, and Hans W. Borchers, ABB Corporate Research.

License: GPL (>= 2)

Uses: Does not use any package
Reverse depends: BivarP, matie, mvord
Reverse suggests: afex, lme4, metafor, optimx, ROI.plugin.optimx, SACOBRA, SPOT

Released over 1 year ago.

7 previous versions



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