Hi all,
As an heavy R (http://www.r-project.org, a very nice statistical package
which is "a bit" to Scheme what Maxima is to Common Lisp) and an
occasional Maxima user (for symbolic computations, etc) I recently came
across a very interesting conference paper by Ross Ihaka (one of the two
original R developers) and Duncan Temple Lang: "Back to the Future: Lisp
as a Base for a Statistical Computing System."
(http://www.stat.auckland.ac.nz/%7Eihaka/downloads/Compstat-2008.pdf). The
paper goes through some of the present limitations of R (not compiled,
arguments passed by values, etc) and argues in favor of a
reimplementation of R as an "M-expression" layer on top of Common
Lisp. This paper triggered my interest in Common Lisp (better late than
never!) and made me realized that I missed a lot about the capabilities
of Maxima. But I would like the opinion of the Maxima's experts here, at
least the ones who have time to read Ihaka and Temple Lang's paper:
aren't they proposing to re-implement Maxima (with a strong statistical
flavor)? If yes, wouldn't it be more economical to adapt to Maxima some
of the coolest features of R?
Christophe
--
Most people are not natural-born statisticians. Left to our own
devices we are not very good at picking out patterns from a sea of
noisy data. To put it another way, we are all too good at picking out
non-existent patterns that happen to suit our purposes.
Bradley Efron & Robert Tibshirani (1993) An Introduction to the Bootstrap
--
Christophe Pouzat
Laboratoire de physiologie c?r?brale
CNRS UMR 8118
UFR biom?dicale de l'Universit? Paris-Descartes
45, rue des Saints-P?res
75006 PARIS
France
tel: +33 (0)1 42 86 38 28
fax: +33 (0)1 42 86 38 30
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web: http://www.biomedicale.univ-paris5.fr/physcerv/C_Pouzat.html