optextras-package: A replacement and extension of the optim() function, plus...

Description Details Author(s) References See Also

Description

Provides a replacement and extension of the optim() function to unify and streamline optimization capabilities in R for smooth, possibly box constrained functions of several or many parameters

The three functions ufn, ugr and uhess wrap corresponding user functions fn, gr, and hess so that these functions can be executed safely (via try()) and also so parameter or function scaling can be applied. The wrapper functions also allow for maximization of functions (via minimization of the negative of the function) using the logical parameter maximize.

There are three test functions, fnchk, grchk, and hesschk, to allow the user function to be tested for validity and correctness. However, no set of tests is exhaustive, and extensions and improvements are welcome. The package numDeriv is used for generation of numerical approximations to derivatives.

Details

Package: optextras
Version: 2012-6.18
Date: 2012-06-18
License: GPL-2
Lazyload: Yes
Depends: numDeriv
Suggests: BB, ucminf, Rcgmin, Rvmmin, minqa, setRNG, dfoptim
Repository: R-Forge
Repository/R-Forge/Project: optimizer

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axsearch     Perform an axial search optimality check
bmchk        Check bounds and masks for parameter constraints
bmstep       Compute the maximum step along a search direction.
fnchk        Test validity of user function
gHgen        Compute gradient and Hessian as a given 
             set of parameters
gHgenb       Compute gradient and Hessian as a given 
             set of parameters appying bounds and masks
grback       Backward numerical gradient approximation
grcentral    Central numerical gradient approximation
grchk        Check that gradient function evaluation 
             matches numerical gradient
grfwd        Forward numerical gradient approximation
grnd         Gradient approximation using \code{numDeriv}
hesschk      Check that Hessian function evaluation 
             matches numerical approximation
kktchk         Check the Karush-Kuhn-Tucker optimality conditions
scalechk   Check scale of initial parameters and bounds

Author(s)

John C Nash <[email protected]> and Ravi Varadhan <[email protected]>

Maintainer: John C Nash <[email protected]>

References

Nash, John C. and Varadhan, Ravi (2011) Unifying Optimization Algorithms to Aid Software System Users: optimx for R, Journal of Statistical Software, publication pending.

See Also

optim


optextras documentation built on May 30, 2017, 8:18 a.m.