On Fri, Dec 3, 2010 at 11:01 AM, Ravi Varadhan <[email protected]> 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: [email protected] > > > -----Original Message----- > From: [email protected] [mailto:[email protected]] > On Behalf Of Duncan Murdoch > Sent: Friday, December 03, 2010 11:13 AM > To: [email protected] > Cc: [email protected] > 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 > > ______________________________________________ > [email protected] mailing list > https://stat.ethz.ch/mailman/listinfo/r-devel > > ______________________________________________ > [email protected] mailing list > https://stat.ethz.ch/mailman/listinfo/r-devel > ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
