Tools to Support Optimization Methods

Documentation for package ‘optextras’ version 2013-10.28

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axsearch	Perform axial search around a supposed minimum and provide diagnostics
bmchk	Check bounds and masks for parameter constraints used in nonlinear optimization
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 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) gradient and hessian
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 (optionally) gradient and hessian
kktc	Check Kuhn Karush Tucker conditions for a supposed function minimum
optextras	A replacement and extension of the optim() function, plus various optimization tools
optsp	Forward difference numerical gradient approximation.
scalecheck	Check the scale of the initial parameters and bounds input to an optimization code used in nonlinear optimization
ufn	Wrap user objective function for optimization tools
ugHgenb	Generate gradient and Hessian for a function at given parameters using function wrappers to control for scaling and inadmissible inputs.
ugr	Wrapper for user gradient function for optimization tools
uhess	Wrapper for user Hessian function for optimization tools