optextras: Tools to Support Optimization Possibly with Bounds and Masks
Version 2016-8.8

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.

AuthorJohn C Nash [aut, cre]
Date of publication2016-08-08 17:08:22
MaintainerJohn C Nash <nashjc@uottawa.ca>
LicenseGPL-2
Version2016-8.8
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("optextras")

Getting started

Package overview

Popular man pages

bmchk: Check bounds and masks for parameter constraints used in...
grback: Backward difference numerical gradient approximation.
grfwd: Forward difference numerical gradient approximation.
grnd: A reorganization of the call to numDeriv grad() function.
hesschk: Run tests, where possible, on user objective function and...
optextras-package: A replacement and extension of the optim() function, plus...
scalechk: Check the scale of the initial parameters and bounds input to...
See all...

All man pages Function index File listing

Man pages

axsearch: Perform axial search around a supposed minimum and provide...
bmchk: Check bounds and masks for parameter constraints used in...
bmstep: Compute the maximum step along a search direction.
fnchk: Run tests, where possible, on user objective function
gHgen: Generate gradient and Hessian for a function at given...
gHgenb: Generate gradient and Hessian for a function at given...
grback: Backward difference numerical gradient approximation.
grcentral: Central difference numerical gradient approximation.
grchk: Run tests, where possible, on user objective function and...
grfwd: Forward difference numerical gradient approximation.
grnd: A reorganization of the call to numDeriv grad() function.
hesschk: Run tests, where possible, on user objective function and...
kktchk: Check Kuhn Karush Tucker conditions for a supposed function...
optextras-package: A replacement and extension of the optim() function, plus...
scalechk: Check the scale of the initial parameters and bounds input to...

Functions

axsearch Man page Source code
bmchk Man page Source code
bmstep Man page Source code
fnchk Man page Source code
gHgen Man page Source code
gHgenb Man page Source code
grback Man page Source code
grcentral Man page Source code
grchk Man page Source code
grfwd Man page Source code
grnd Man page Source code
hesschk Man page Source code
kktchk Man page Source code
optextras Man page
optsp Man page
scalechk Man page Source code

Files

po
po/R-optextras.pot
po/R-ko.po
tests
tests/tgrchk.R
tests/tfnchk.R
tests/tkktc.R
NAMESPACE
NEWS
R
R/kktchk.R
R/bmstep.R
R/grcentral.R
R/grnd.R
R/fnchk.R
R/gHgenb.R
R/hesschk.R
R/axsearch.R
R/bmchk.R
R/grchk.R
R/grfwd.R
R/scalechk.R
R/gHgen.R
R/zzz.R
R/grback.R
MD5
DESCRIPTION
man
man/hesschk.Rd
man/grback.Rd
man/grchk.Rd
man/gHgen.Rd
man/optextras-package.Rd
man/grnd.Rd
man/grfwd.Rd
man/kktchk.Rd
man/bmstep.Rd
man/fnchk.Rd
man/gHgenb.Rd
man/axsearch.Rd
man/scalechk.Rd
man/grcentral.Rd
man/bmchk.Rd
optextras documentation built on May 20, 2017, 5:49 a.m.

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