John Whittington wrote: > > At 11:51 05/08/99 -0700, Karsten M. Self wrote:

<snip>

> >As I'm given to understand many SAS/STAT products, they are essentially > >based on IML and matrix manipulations. I'm again largely ignorant of > >the area, but if a procedure requires loading an entire matrix in > >memory, or exploding it out (my mind goes to the analog of a cartesian > >join under SQL, I'm under the impression that matrix inversion is > >similar in scope), then even moderate quantities of data may introduce > >very high resource demands.

> What I don't know is exactly how SAS deals with rank-based activities such > as 'non-parametric tests' (e.g. NPAR1WAY), or even the rank-based > statistics provided by UNIVARIATE. On the face of it, these activities > appear to require sorts of the entire dataset (or dervivations thereof, > with the same number of obs), and storage of the resultant stored dataset.

I don't even know what NPAR1WAY is or does (I'm a programmer, dammit...), much less how it works.

Univariate, if I remember my basic stats well enough, can generate most of its stats by computing statistical moments -- single point measures -- for variables, for most statistics. Certainly this works for mean, n, standard deviation, and measures derived from these. A short array will do for accumulating extreme values (the n largest and smallest values). Mode, median, and percentiles are a different animal AFAIK, thought there are probably some algorithmic shortcuts. My earlier investigation of BASS (Jeff Bass's early PC-based SAS run-alike) showed that most of the algorithms in use in SAS, at least at the time BASS was created, were based on published work. According to the Procedure Manual, p 625, this is:

Fisher, R.A. (1973), /Statistical Methods for Research Workers/, 14th Edition, New York: Hafner Publishing Company.

Amazon.com lists this as out-of-print (http://www.amazon.com/exec/obidos/ASIN/0050021702).

-- Karsten M. Self (kmself@ix.netcom.com) What part of "Gestalt" don't you understand?

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