optimx2023-10.21 package

Expanded Replacement and Extension of the 'optim' Function

bmchk

Check bounds and masks for parameter constraints used in nonlinear opt...

axsearch

Perform axial search around a supposed MINIMUM and provide diagnostics

bmstep

Compute the maximum step along a search direction.

checksolver

Test if requested solver is present

coef.opm

Summarize opm object

ctrldefault

set control defaults

fnchk

Run tests, where possible, on user objective function

gHgen

Generate gradient and Hessian for a function at given parameters.

gHgenb

Generate gradient and Hessian for a function at given parameters.

grback

Backward difference numerical gradient approximation.

grcentral

Central difference numerical gradient approximation.

grchk

Run tests, where possible, on user objective function and (optionally)...

grfwd

Forward difference numerical gradient approximation.

grnd

A reorganization of the call to numDeriv grad() function.

grpracma

A reorganization of the call to numDeriv grad() function.

hesschk

Run tests, where possible, on user objective function and (optionally)...

hjn

Compact R Implementation of Hooke and Jeeves Pattern Search Optimizati...

kktchk

Check Kuhn Karush Tucker conditions for a supposed function minimum

multistart

General-purpose optimization - multiple starts

opm

General-purpose optimization

optchk

General-purpose optimization

optimr

General-purpose optimization

optimx-package

A replacement and extension of the optim() function, plus various opti...

optimx

General-purpose optimization

polyopt

General-purpose optimization - sequential application of methods

proptimr

Compact display of an optimr() result object

Rcgmin

An R implementation of a nonlinear conjugate gradient algorithm with t...

Rcgminb

An R implementation of a bounded nonlinear conjugate gradient algorith...

Rcgminu

An R implementation of an unconstrained nonlinear conjugate gradient a...

Rvmmin

Variable metric nonlinear function minimization, driver.

Rvmminb

Variable metric nonlinear function minimization with bounds constraint...

Rvmminu

Variable metric nonlinear function minimization, unconstrained

scalechk

Check the scale of the initial parameters and bounds input to an optim...

snewton

Safeguarded Newton methods for function minimization using R functions...

summary.optimx

Summarize optimx object

tn

Truncated Newton minimization of an unconstrained function.

tnbc

Truncated Newton function minimization with bounds constraints

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.

  • Maintainer: John C Nash
  • License: GPL-2
  • Last published: 2023-10-24