[Rd] Competing with one's own work

Douglas Bates bates at stat.wisc.edu
Fri Dec 3 19:28:03 CET 2010

On Fri, Dec 3, 2010 at 11:01 AM, Ravi Varadhan <rvaradhan at jhmi.edu> wrote:
> 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.

constrOptim is in the stats package, not the base package.  Functions
that are already in the required packages are maintained by R core.
If you know of bugs in such functions you should report them.  Because
there is a heavy burden in maintaining the large corpus of software in
R and its required packages, additions are viewed skeptically,
Adopting new capabilities and new code in a required package like
stats means that some member of R core has to be willing to maintain
it.  If the capabilities can be incorporated in a contributed package
then that is the preferred method of extending R. The burden of
maintaining the code, fixing bugs or other infelicities, etc. is on
the package maintainer.

I don't see anything in what you are proposing that could not be
incorporated in a contributed package.

> 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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