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st: RE: The Future of Statistical Computing


From   "Nick Cox" <[email protected]>
To   <[email protected]>
Subject   st: RE: The Future of Statistical Computing
Date   Thu, 22 Jan 2009 19:18:01 -0000

Thanks to Stas for publicising this paper. My take is the opposite of
his: 
Data mining seems to me far more over-hyped than statistical software. 

I reviewed Leland's book for the Journal of Statistical Software in
2007. 
He exercised his right to reply. Both pieces are accessible at 

<http://www.jstatsoft.org/v17/b03> 

By an odd kind of symmetry, that makes me wonder whether the vendors of
competitor software will be allowed to reply in due course to Leland's
comments in this paper! 

The Stata write-up doesn't look outrageous to me. (Clearly Leland
couldn't bring himself to compliment Stata's graphics.) 
But it is behind the curve in not mentioning Mata. 

Nick 
[email protected] 

Stas Kolenikov

The recent issue of Technometrics (vol 50 (4), I've just received it)
has an extensive article with the title in the subject line by Leland
Wilkinson, an extremely smart guy at the interface of statistics and
computer science, the author of SYSTAT and "The Grammar of Graphics"
book (totally incomprehensible to me, but a delight for Vince W, I am
sure :)). The link is http://pubs.amstat.org/toc/tech/50/4. He says,
"Statisticians interested in statistical computing and its future
incarnations will have to engage in joint research with computer
scientists to continue to have an influence." Catching up has been the
situation in data mining for some while now; and it may look like
advances in computing everywhere might phase statisticians out.

There are two paragraphs about Stata (ranked eighth in revenues after
SAS, SPSS, Matlab, Minitab, Statistica, S-Plus and JMP):

"Stata was originally the product of Bill Gould and a small group of
economists from UCLA. It has grown to be a full-featured analytic
company. The distinctive appeal of the package is its expressive and
concise programming language, based on C. Stata's unusual strengths
are in discrete variable modeling, longitudinal/panel designs,
survival analysis, time series analysis, and survey statistics.

Like S-PLUS, Stata will have to deal with the growth of R in its own
field-programmable statistics and data analysis. Unlike S-PLUS,
however, Stata's peculiar strengths and language are different enough
from R to make it a viable alternative, particularly for
economists.Moreover, the Stata user community is intensely loyal, so
we should expect Stata to continue to grow at a respectable rate."

An interesting reading. Stata developers including the top SSC
contributors might want to check it out.

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