[R--gR] Modelformulae

A few comments - just to clear my mind.

Dear gR-folks

The Danish gR-gang have been talking about describing a model language for
graphical models that

1) could specify at least chain graph models, based on the most general
hierarchical mixed models as
described in Lauritzen (1996) [my book], section 6.4, pages 199-216. (More
general than MIM-models).
 

Are we limiting the discussion to the Conditionally Gaussian(CG) case 
with independent and identically distributed observations?
That would make life much more easy and clearly rule out X*Y*Z between 
continuous variables.
And I have no problem with interpreting "~" as "log f ~" as long as we 
are careful to include quadratic terms of  continuos variables.
But it also rules out things like ~Z+log(X)  and is far from having the 
same flexibility as the BUGS syntax.
We might allow ~Z*(Z+log(X))|X  and thereby leaving CG, but sticking to 
gaussian error.

If we want a more general BUGS/glim-like syntax, we need to consider,
how to include information on link and errordistribution. And it would 
be nice
to facilitate correlation across unit, e.g. by allowing ~X*B(X)|B(X), 
where B is the backshift operator.

Regards, svante

----------------------------------------------------
Poul Svante Eriksen, office G1-113
Department of Mathematical Sciences
Aalborg University
Fredrik Bajers Vej 7G, DK-9220 Aalborg East, Denmark
tel.: (+45) 96358868