From: Ravi Varadhan (email@example.com)
Date: Tue 04 May 2004 - 02:12:58 EST
Along the lines of this thread, I was wondering about the usefulness of
putting together a package for numerical differentiation, to perform
tasks such as gradient, jacobian, and hessian calculations for exact
functions, as well as for noisy functions (via some type of smoothing).
Based on finite difference calculus, I have written a number of
(simple) R functions for gradient, jacobian, and hessian computations
of different orders of accuracy. If such functions aren't already
available, I could supply these to whoever may be interested in
undertaking this project.
----- Original Message -----
From: Paul Gilbert <firstname.lastname@example.org>
Date: Friday, April 30, 2004 2:19 pm
Subject: Re: [R] numericDeriv
> Jean Eid wrote:
> >Dear All,
> >I am trying to solve a Generalized Method of Moments problem which
> >necessitate the gradient of moments computation to get the
> >standard errors of estimates.
> >I know optim does not output the gradient, but I can use
> numericDeriv to
> >get that. My question is: is this the best function to do this?
> 'Best' depends on what you want. If you want an accurate numerical
> estimate of the gradient then you might look at the program
> gradRichardson in the curve package of the dseplus bundle in the
> area of CRAN. It uses Richarson extrapolation to improve the
> However, this is not the program to use if you want a quick
> estimate of the gradient. Most anything else you might think of
> will be quicker.
> There are some other programs around too. A year or two ago there
> some discussion of putting various gradient calculation techniques
> together in one place. I don't think anything has happen yet.
> Paul Gilbert
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