dfoptim: Derivative-Free Optimization

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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.

Author
Ravi Varadhan, Johns Hopkins University, and Hans W. Borchers, ABB Corporate Research.
Date of publication
2016-07-10 17:01:39
Maintainer
Ravi Varadhan <ravi.varadhan@jhu.edu>
License
GPL (>= 2)
Version
2016.7-1
URLs

View on CRAN

Man pages

dfoptim-package
Derivative-Free Optimization
hookejeeves
Hooke-Jeeves derivative-free minimization algorithm
nmkb
Nelder-Mead optimziation algorithm for derivative-free...

Files in this package

dfoptim
dfoptim/NAMESPACE
dfoptim/demo
dfoptim/demo/00Index
dfoptim/demo/dfoptim.R
dfoptim/NEWS
dfoptim/R
dfoptim/R/hjk.R
dfoptim/R/nmkb.R
dfoptim/R/nmk.R
dfoptim/R/hjkb.R
dfoptim/MD5
dfoptim/DESCRIPTION
dfoptim/man
dfoptim/man/hookejeeves.Rd
dfoptim/man/dfoptim-package.Rd
dfoptim/man/nmkb.Rd