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I've written a big review of R. Can I get some feedback?

Actually, some of us use R as a quite effective tool for testing and evaluating optimization,
nonlinear least squares codes, and some other numerical algorithms, as well as for one-off
or at least limited number of runs cases. R allows a lot of flexibility in trying out ideas
for such tasks where the goal is to check that the solution is a good one. Reliability
rather than speed.

My experience is that R is at least as good a programming environment for this as any other
I've used e.g., Matlab, Fortran, Pascal, BASIC, C, Python, and a few others now of historical
interest only. Who's up for Modula2, APL, QNial, Algol, Algol68, forth, or that wonderful tool,
Assembler? I've used them all, and now prefer R. I might be tempted to try Julia once it
stabilizes. For now it seems to have a lot of similarities to a greased piglet at a fairground
competition.

I do almost no data analysis with R myself, though others do, I believe, use my software in that
pursuit. Given that some of your complaints about R nuisances have a basis, I'll simply note that all
programming languages have their annoyances. At least R is community-based and we can provide those
wonderful "small reproducible examples" and quite often get improvements, and if we offer good
patches, they do get into the distributed code. I've managed to do that in the space of a few
months with R. A reported bug in Excel ... still there I think after over 2 decades. I gave up
waiting.

As others have written in replies to your request, it is worth focusing on what may be fixable and
seeing what can be done, either to fix those issues or to document things to help users. And I
think it sensible to assume ALL of us are novices in areas beyond where we toil daily. R users
cover a huge range of interests, so experts in one aspect are beginners in another.

John Nash
On 2022-04-12 17:31, Reece Goding wrote: