Re: [Rd] Competing with one's own work

From: Ravi Varadhan <rvaradhan_at_jhmi.edu>
Date: Fri, 03 Dec 2010 12:01:15 -0500

Dear Duncan,

What constitutes a convincing argument for making significant changes? Taking the example of optimization algorithms (say, for smooth objective functions), how does one make a convincing argument that a particular class of algorithms are "better" than another class? This can be a difficult task, but quite doable with good benchmarking practices.

Supposing for the moment that such a convincing argument has been made, is that sufficient to get the R-core to act upon it? Are there compelling factors other than just "algorithm A is better than algorithm B"?

I'd think that the argument is relatively easy if the need for the change is driven by consumer demand. But, even here I am not sure how to make an argument to the R-core to consider the big changes. For example, there is a reasonable demand for constrained (smooth) optimization algorithms in R (based on R-help queries). Currently, there are only 3 packages that can handle this. However, in the base distribution only `constrOptim' function is provided, which cannot handle anything more than linear, inequality constraints. I think that the base distribution needs to have a package for constrained optimization that can handle linear/nonlinear and equality/inequality constraints.

John, thanks for raising an important issue.

Thanks & Best,
Ravi.



Ravi Varadhan, Ph.D.
Assistant Professor,
Division of Geriatric Medicine and Gerontology School of Medicine Johns Hopkins University

Ph. (410) 502-2619
email: rvaradhan_at_jhmi.edu

-----Original Message-----
From: r-devel-bounces_at_r-project.org [mailto:r-devel-bounces_at_r-project.org] On Behalf Of Duncan Murdoch
Sent: Friday, December 03, 2010 11:13 AM To: nashjc_at_uottawa.ca
Cc: r-devel_at_r-project.org
Subject: Re: [Rd] Competing with one's own work

On 03/12/2010 10:57 AM, Prof. John C Nash wrote:
> No, this is not about Rcpp, but a comment in that overly long discussion
raised a question
> that has been in my mind for a while.
>
> This is that one may have work that is used in R in the base functionality
and there are
> improvements that should be incorporated.
>
> For me, this concerns the BFGS, Nelder-Mead and CG options of optim(),
which are based on
> the 1990 edition (Pascal codes) of my 1979 book "Compact numerical
methods...", which were
> themselves derived from other people's work. By the time Brian Ripley took
that work (with
> permission, even though not strictly required. Thanks!) there were already
some
> improvements to these same algorithms (mainly bounds and masks) in the
BASIC codes of the
> 1987 book by Mary Walker-Smith and I. However, BASIC to R is not something
I'd wish on
> anyone.
>
> Now there are some R packages, including some I've been working on, that
do offer
> improvements on the optim() offerings. I would not say mine are yet fully
ready for
> incorporation into the base, but they are pretty close. Equally I think
some of the tools
> in the base should be deprecated and users encouraged to try other
routines. It is also
> getting more and more important that novice users be provided with
sensible guidance and
> robust default settings and choices. In many areas, users are faced with
more choice than
> is efficient for the majority of problems.
>
> My question is: How should such changes be suggested / assisted? It seems
to me that this
> is beyond a simple feature request. Some discussion on pros and cons would
be appropriate,
> and those like myself who are familiar with particular tools can and
should offer help.
>
> Alternatively, is there a document available in the style "Writing R
Extensions" that has
> a title like "How the R Base Packages are Updated"? A brief search was
negative.
>
> I'm happy to compete with my own prior work to provide improvements. It
would be nice to
> see some of those improvements become the benchmark for further progress.

There are answers at many different levels to your questions. The simplest is that base packages are part of R, so they get updated when a member of R Core updates them, and the updates get released when a new version of R is released.

So if you want a change, you need to convince a member of the core to make it. Pointing out a bug is the easiest way to do this: bugs usually get fixed quickly, if they are clearly demonstrated.

If you want a bigger change, you need to make a convincing argument in favour of it. If you pick a topic that is of particular interest to one core member, and you can convince him to make the change, then it will happen. If pick some obscure topic that's not of interest to anyone, you'll need a very strong argument to make it interesting. Part of any of these arguments is explaining why the change needs to be made to the base, why it can't just be published in a contributed package. (That's why bug fixes are easy, and big additions to the base packages are not.)

Duncan Murdoch



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