Expanded Replacement and Extension of the 'optim' Function
Perform axial search around a supposed MINIMUM and provide diagnostics
Check bounds and masks for parameter constraints used in nonlinear opt...
Generate gradient and Hessian for a function at given parameters.
A reorganization of the call to the pracma grad() function.
Compute the maximum step along a search direction.
Test if requested solver is present
Summarize opm object
set control defaults
Run tests, where possible, on user objective function
Generate gradient and Hessian for a function at given parameters.
Backward difference numerical gradient approximation.
Central difference numerical gradient approximation.
Run tests, where possible, on user objective function and (optionally)...
Forward difference numerical gradient approximation.
A reorganization of the call to numDeriv grad() function.
Run tests, where possible, on user objective function and (optionally)...
Compact R Implementation of Hooke and Jeeves Pattern Search Optimizati...
Check Kuhn Karush Tucker conditions for a supposed function minimum
General-purpose optimization - multiple starts
An R implementation of a Dai / Yuan nonlinear conjugate gradient algor...
Variable metric nonlinear function minimization, driver.
General-purpose optimization
Extract optim() solution for one method of opm() result
General-purpose optimization
General-purpose optimization
A replacement and extension of the optim() function, plus various opti...
General-purpose optimization
General-purpose optimization - sequential application of methods
Compact display of an optimr() result object
An R implementation of a Dai / Yuan nonlinear conjugate gradient algor...
Truncated Newton function minimization
Variable metric nonlinear function minimization, driver.
Check the scale of the initial parameters and bounds input to an optim...
Safeguarded Newton methods for function minimization using R functions...
Summarize optimx object
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.