dfoptim v2018.2-1
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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.
Functions in dfoptim
| Name | Description | |
| dfoptim | Derivative-Free Optimization | |
| nmk | Nelder-Mead optimziation algorithm for derivative-free optimization | |
| hjk | Hooke-Jeeves derivative-free minimization algorithm | |
| No Results! | ||
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Details
| Type | Package |
| Date | 2018-02-18 |
| URL | http://www.jhsph.edu/agingandhealth/People/Faculty_personal_pages/Varadhan.html |
| License | GPL (>= 2) |
| LazyLoad | yes |
| Repository | CRAN |
| NeedsCompilation | no |
| Packaged | 2018-04-01 23:02:47 UTC; rvaradhan |
| Date/Publication | 2018-04-02 09:37:48 UTC |
| depends | R (>= 2.10.1) |
| Contributors | Ravi Varadhan, Johns University, Hans Borchers, ABB Research |
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[](http://www.rdocumentation.org/packages/dfoptim)