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Tools to assist in safely applying user generated objective and derivative function to optimization programs. These are primarily function minimization methods with at most bounds and masks on the parameters. Provides a way to check the basic computation of objective functions that the user provides, along with proposed gradient and Hessian functions, as well as to wrap such functions to avoid failures when inadmissible parameters are provided. Check bounds and masks. Check scaling or optimality conditions. Perform an axial search to seek lower points on the objective function surface. Includes forward, central and backward gradient approximation codes.
| Version: | 2019-12.4 |
| Imports: | numDeriv, utils |
| Published: | 2019-12-20 |
| DOI: | 10.32614/CRAN.package.optextras |
| Author: | John C Nash [aut, cre] |
| Maintainer: | John C Nash <nashjc at uottawa.ca> |
| License: | GPL-2 |
| NeedsCompilation: | no |
| Materials: | NEWS |
| CRAN checks: | optextras results |
| Reference manual: | optextras.pdf |
| Package source: | optextras_2019-12.4.tar.gz |
| Windows binaries: | r-devel: optextras_2019-12.4.zip, r-release: optextras_2019-12.4.zip, r-oldrel: optextras_2019-12.4.zip |
| macOS binaries: | r-release (arm64): optextras_2019-12.4.tgz, r-oldrel (arm64): optextras_2019-12.4.tgz, r-release (x86_64): optextras_2019-12.4.tgz, r-oldrel (x86_64): optextras_2019-12.4.tgz |
| Old sources: | optextras archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.