Dear Karl-Dieter (IIRC, apologies if not...) I saw your comments to my answer to William. It gives useful points, but I need more time to propose a consistent solution.
One more (side) point : I think that what is called currently statistics is currently evolving to become a discipline aiming at proposing and comparing unobservable structures explaining observed data (with much more emphasis on the probability than before) . From this point of view, the use of formal tools manipulating such structures is of great importance : logics (not necessarily Boolean), algebraic structures, graphs, etc.. will become important to the practicing applied statistician. Hence the importance of a toolbox enabling us to make *conjoint* use of both sets of tools. And, oh, by the way, numerical analysis has not totally displaced formal methods : to be able to get formal solutions to an integration problem or a differential equations system is still damn important... -- Emmanuel Charpentier Le mardi 1 novembre 2016 20:36:59 UTC+1, kcrisman a écrit : > > > Nobody is suggesting deprecating the potential to use Sage+R. >>> >> >> That's replacing "It's there" by "It can be done". Not the same thing... >> unless you're a theologian or a politician. >> >> > Thank you. > > >> >> A third point, distinct from the previous two, is that William deems the >> current pexpect interface to be insufficient. Having suffered with it, I >> tend to concur. But I think that the pexpect() interface is *still* useful. >> >>> >>> > Correct. > > >> >>> >> >>> I've never once heard of anybody actually trying to use >>> Sage + R yet. >> >> >> Can you hear me now ? >> >> > > I definitely have, and I have heard from those who do. Don't ask me for a > detailed list. But: > > https://ask.sagemath.org/question/9851/passing-array-from-sage-to-r-and-back-again/ > https://ask.sagemath.org/question/8229/inter-mixing-sage-and-r/ > https://ask.sagemath.org/question/8375/converting-r-variables-to-sage/ > >> >> It adds a lot : availability of tools much better at expressing >> *structures* than anything available on the R side (thonk graph theory, >> symbolic computation, etc...). That's no as popular among applied >> statisticians as computing "tests p-values" (the present), but remains the >> core problem of statistics ("given some data, what is the "right" structure >> that accounts for them ? "., i. e. the future...). >> >>> >>> > > Right, R is so much more than stats. It's just ... everything you every > wanted for processing all sorts of numerical data. Often the only > open-source way to deal with a lot of stuff is via some random R package. > And those things then would far easier be processed in R and sent back to > Sage. I am very excited about (someday) learning how to use pandas > better, as a Python-native setup, but for practical purposes there is just > too much stuff available with R for many people to just abandon it. > +++ > Anyway, count this as a vote for at the very least maintaining the current > R interface for continued compatibility for a longer period than the usual > deprecation, though I think that changing that would really change what was > available in Sage, for the poorer. If the rpy2 roadblocks can be overcome, > obviously so much the better. > -- You received this message because you are subscribed to the Google Groups "sage-devel" group. To unsubscribe from this group and stop receiving emails from it, send an email to sage-devel+unsubscr...@googlegroups.com. To post to this group, send email to sage-devel@googlegroups.com. Visit this group at https://groups.google.com/group/sage-devel. For more options, visit https://groups.google.com/d/optout.
