I read this code last night, and the existing implementation is
straightforward, but doesn't handle some of the more complicated
things:

sigma restricted encoding (this seems tough - might be worth leaving
as a later enhancement)
interactions
 - which lead to:
   nested designs
   [partial] factorial designs
   mixture surface models (i think they're called - regression with
interactions)

I'm not sure what the ideal spec for a routine building a design
matrix is. The existing code does everything you need at a basic
level, provided you have all your independent variables, but it
doesn't introduce terms to handle interactions. Something on top
perhaps needs to take a model spec like A(B) C C*D or whatever and
turn that into a set of independent variables for the design matrix
routine to handle.

I haven't really thought this through yet, but I am hoping to work on it.

Ed

2008/6/7 John Darrington <[EMAIL PROTECTED]>:
> On Thu, Jun 05, 2008 at 05:05:38PM -0400, Jason Stover wrote:
>
>     The big
>     problem there is the "accounting" problem of mapping values of a 
> qualitative
>     variable back and forth to vectors with binary entries.
>
> I don't understand why this is a "big" problem, but perhaps I'm being
> naive.  Would it be possible to have a brief specification for the
> problem.
>
> J'
>
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