Permit me to echo Bj??rn-Helge Mevik's thanks.
I've been telling people that R is rapidly becoming the platform
of choice for new statistical algorithm development for many reasons.
* First, it gives someone almost instant access to many of the
leading international experts in statistical computing. This includes
free access to some of the best code available for almost any
statistical application.
* Second, it provides new algorithm developers with an easy way to
solicit feedback on their code from many others, including not only the
recognized experts in statistical computing but many others who know a
lot but may not be as well known.
* Third, distributing an R package is a type of publication. It
may not count in the peer review process, but it might reach more people
and build one's reputation faster than a standard publication. Also, I
wonder how this impacts how easy it might be to get something published
in a more traditional way?
At a conference recently, someone claimed that universities are
dumping SAS, SPSS, Minitab, etc., for R because R is free and the
alternatives are not. I don't know the extent to which this is true,
but I can see another reason for doing this: It's incredibly easy for
instructors to share their latest code with their students.
Does anyone have any thoughts on this?
Comments?
Best Wishes,
Spencer Graves
Bj??rn-Helge Mevik wrote:
I'd like to thank the developers in the Core Team for their great
work! R has become an invaluable and indispensible tool for (at least)
me, much thanks to the hard and good work of the Core Team.