grback: Backward difference numerical gradient approximation.

In optimx: Expanded Replacement and Extension of the 'optim' Function

Backward difference numerical gradient approximation.

Description

grback computes the backward difference approximation to the gradient of user function userfn.

Usage

   grback(par, userfn, fbase=NULL, env=optsp, ...)

Arguments

par	parameters to the user objective function userfn
userfn	User-supplied objective function
fbase	The value of the function at the parameters, else NULL. This is to save recomputing the function at this point.
env	Environment for scratchpad items (like deps for approximation control in this routine). Default optsp.
...	optional arguments passed to the objective function.

Details

Package:	grback
Depends:	R (>= 2.6.1)
License:	GPL Version 2.

Value

grback returns a single vector object df which approximates the gradient of userfn at the parameters par. The approximation is controlled by a global value optderiveps that is set when the package is attached.

Author(s)

John C. Nash

Examples

cat("Example of use of grback\n")

myfn<-function(xx, shift=100){
    ii<-1:length(xx)
    result<-shift+sum(xx^ii)
}

xx<-c(1,2,3,4)
ii<-1:length(xx)
print(xx)
gn<-grback(xx,myfn, shift=0)
print(gn)
ga<-ii*xx^(ii-1)
cat("compare to analytic gradient:\n")
print(ga)

cat("change the step parameter to 1e-4\n")
optsp$deps <- 1e-4
gn2<-grback(xx,myfn, shift=0)
print(gn2)

optimx documentation built on Oct. 24, 2023, 5:06 p.m.