LispStat, R and ViSta [was: Re: Status?]

[uluru@email.unc.edu]

I have been taking a break for the last month or so, and am only just
now catching up on my email.  Otherwise, I would have joined this
discussion earlier.  And... I apologize for the length of this, but I
don't think it is overly long.

>From the amount of activity in the LispStat news group (none), it seems
that LispStat is dead. We all know that Luke is working on R and not on
LispStat, and that Jan has switched UCLA over from LispStat to R. And we
have not heard from users of LispStat for some time.  So, it seems no
one is using LispStat.

For me, at least, this is not the case. As the developer of ViSta, I
have and still am using LispStat a great deal. In fact, I cannot
conceive of doing what I do with any other system.  

Of course, since I use it so much, I am very aware of LispStat's
strengths and weaknesses, and want to add my views to the discussion.
However, I spend all my time using only LispStat, so I can't make any
comparisons to R or to any other systems.

To me, the strengths of LispStat are:
1) The dynamic, highly interactive graphics
2) The object system
3) Lisp language and byte compiler

These strengths make LispStat an ideal system for implementing
statistical systems. It is less suited for doing statistical analysis.
As a result, the most significant uses of LispStat have been statistical
systems such as Arc and ViSta.

In the work I've done with LispStat,  ViSta's spreadplot architecture is
the best example of LispStat being used to implement a statistical
(sub)system (described in a forthcoming JCGS paper by myself, Pedro
Valero, Richard Faldowski and Carla Bann). 

The weaknesses of LispStat are:
1) No high-level analysis modules
2) No standards for data sets, models, etc.
3) No user-oriented data manipulation language
4) Totally inadequate documentation
5) Poor or non-existant printing 
6) No static graphic manipulation facilities
7) The underlying operating system interfaces are old.

ViSta attempts to take care of these weaknesses, with varying degrees of
success. Specifically:
1) ViSta has high-level analysis plugins. The method for writing these
plugins is documented. I believe this very well solves the first weakness. 
2) ViSta's statistical object architecture -- a hierarchy of objects
that include datasets, datasheets, data editors, transformations,
analysis methods, models and plugins --- solves the lack of standards
for such things. The implementation is slow for data objects and needs
to be re-architected. The implementation for the others is more than
adequate.
3) At the suggestion of Sandy Weisberg, I have incorporated PARCIL, a
C-to-Lisp Parser. This allows users to type a=2*(b+c)^2 rather than the
awkward lisp equivalent:
(setf a (^ (* 2 (+ b c)) 2)) 
(I'm sorry I can't give a proper reference to PARCIL, I'm not at home).
4) Pedro Valero, Gabriel Molina, Michael Friendly and I, in various
combinations, are working on the documentation problem.
5) Printing, while better than LispStat, is still not adequate.
6) Static graphics manipulation, as in SAS (and, apparently R), is
totally lacking.
7) Nothing has been done about this.

(Note that the newest version of ViSta use a modified version of
LispStat that only works under Windows, so that Mac/Unix users don't
have all the new features. This problem can be fixed by someone familiar
with LispStat and Unix.)

I am very interested in an effort to combine the strengths of LispStat
and R, but have no clue how it would be done.  From my viewpoint,
though, it would need to add the three strengths of LispStat (Lisp,
Objects and Dynamic Graphics) to the existing R environment, and it
would need to work in all three supported environments -- Windows, Mac,
and Linux/Unix

Anyone know how to do that?

Forrest
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