optimx v2020-4.2

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Expanded Replacement and Extension of the 'optim' Function

Provides a replacement and extension of the optim() function to call to several function minimization codes in R in a single statement. These methods handle smooth, possibly box constrained functions of several or many parameters. Note that function 'optimr()' was prepared to simplify the incorporation of minimization codes going forward. Also implements some utility codes and some extra solvers, including safeguarded Newton methods. Many methods previously separate are now included here. This is the version for CRAN.

Functions in optimx

Name Description
bmstep Compute the maximum step along a search direction.
checksolver Test if requested solver is present
axsearch Perform axial search around a supposed minimum and provide diagnostics
Rvmminb Variable metric nonlinear function minimization with bounds constraints
grcentral Central difference numerical gradient approximation.
Rcgminu An R implementation of an unconstrained nonlinear conjugate gradient algorithm with the Dai / Yuan update and restart. Based on Nash (1979) Algorithm 22 for its main structure. CALL THIS VIA Rcgmin AND DO NOT USE DIRECTLY.
Rcgminb An R implementation of a bounded nonlinear conjugate gradient algorithm with the Dai / Yuan update and restart. Based on Nash (1979) Algorithm 22 for its main structure. CALL THIS VIA Rcgmin AND DO NOT USE DIRECTLY.
coef Summarize opm object
Rvmminu Variable metric nonlinear function minimization, unconstrained
ctrldefault set control defaults
Rvmmin Variable metric nonlinear function minimization, driver.
Rcgmin An R implementation of a nonlinear conjugate gradient algorithm with the Dai / Yuan update and restart. Based on Nash (1979) Algorithm 22 for its main structure.
bmchk Check bounds and masks for parameter constraints used in nonlinear optimization
grback Backward difference numerical gradient approximation.
gHgenb Generate gradient and Hessian for a function at given parameters.
grfwd Forward difference numerical gradient approximation.
optchk General-purpose optimization
optimx-package A replacement and extension of the optim() function, plus various optimization tools
fnchk Run tests, where possible, on user objective function
hesschk Run tests, where possible, on user objective function and (optionally) gradient and hessian
grnd A reorganization of the call to numDeriv grad() function.
opm General-purpose optimization
optimx General-purpose optimization
grchk Run tests, where possible, on user objective function and (optionally) gradient and hessian
gHgen Generate gradient and Hessian for a function at given parameters.
snewton Safeguarded Newton methods for function minimization using R functions.
hjn Compact R Implementation of Hooke and Jeeves Pattern Search Optimization
proptimr Compact display of an optimr() result object
summary.optimx Summarize optimx object
polyopt General-purpose optimization - sequential application of methods
multistart General-purpose optimization - multiple starts
optimr General-purpose optimization
kktchk Check Kuhn Karush Tucker conditions for a supposed function minimum
tn Truncated Newton minimization of an unconstrained function.
tnbc Truncated Newton function minimization with bounds constraints
scalechk Check the scale of the initial parameters and bounds input to an optimization code used in nonlinear optimization
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Vignettes of optimx

Name
Extend-optimx.Rmd
Extend-optimx.bib
Rvmmin.Rmd
Rvmmin.bib
SNewton.Rmd
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Details

Date 2020-04-02
License GPL-2
LazyLoad Yes
NeedsCompilation no
VignetteBuilder knitr
Packaged 2020-04-02 22:18:54 UTC; john
Repository CRAN
Date/Publication 2020-04-08 14:20:02 UTC

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