| optextras-package {optextras} | R Documentation |
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.
| 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 |
Index:
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
kktc Check the Karush-Kuhn-Tucker optimality conditions
scalecheck Check scale of initial parameters and bounds
ufn Wrapper for user objective function
ugr Wrapper for user gradient function
ugHgenb Compute gradient and Hessian as a given
set of parameters appying bounds and masks
but using the opx12env list of fn, gr, and
hess. Note FIXED name opx12env
uhess Wrapper for user Hessian function
John C Nash <nashjc@uottawa.ca> and Ravi Varadhan <RVaradhan@jhmi.edu>
Maintainer: John C Nash <nashjc@uottawa.ca>
Nash, John C. and Varadhan, Ravi (2011) Unifying Optimization Algorithms to Aid Software System Users: optimx for R, Journal of Statistical Software, publication pending.
optim