[Developers] Need for simpler way to describe the kind of simple mixed models most people are used to.

[dave fournier]

I think we should develop the machinery needed to construct linear
predictors from data in a csv file. I wonder what all is involved.
One thing we need is a "contrast" object.  This is a vector v
parameterized in such a way that sum(v)=0.  For the separable function
to be efficient one want to pass only the  necessary v_i's to the
separable function.  So for example we can parameterize v as

    v_i =w_i -mean(w)


the w_i are the independent variables but the derivative stuff can be
done in terms of the v_i and the derivatives for the w_i calculated from
the v_i just when they are needed (ie some kind of interface needs to
accomplish this.)  Also a penalty like

        100*square(sum(w))

is added so that the problem is not degenerate.

One problem is how to parse the csv file. Hopefully should is existing
software for this we can use.

I think if we can make this all pretty simple we can get a lot more
interest from R users.



-- 
David A. Fournier
P.O. Box 2040,
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http://otter-rsch.com