Thread Subject: Re: Give me a Regression Problem

On Jul 19, 4:22=A0pm, Greg Heath <he...@alumni.brown.edu> wrote:
> On Jul 19, 9:22 am, baldrick <philbrier...@hotmail.com> wrote:
>
>
>
>
>
> > On Jul 19, 9:11 am, Greg Heath <he...@alumni.brown.edu> wrote:
> > > On Jul 18, 1:28 pm, paulvbi...@gmail.com wrote:
> > > -------SNIP
>
> > > > I just reran the SVD PNN with 3 and 6 missing and with Zaknich
> > > > weighting active and get R2=3D0.9129 which is close to the answer w=
ith
> > > > all the variables of R2=3D0.9217 (Zaknich weighting active) which m=
ight
> > > > just might indicate maybe all the variables should be included
>
> > > I wouldn't say that (See below).
>
> > > >but
> > > > this is not clear to me. =A0Likely there are some subtle second ord=
er
> > > > interaction effects here, minor for sure, but a little influence
>
> > > Since my quadratic models obtained R^2 ~ 0.8, I think the effects
> > > are higher order than 2nd.
>
> > > > but as Greg says one may not be able to "prove" this also
>
> > > I think the best you can do is reject or fail to reject a null
> > > hypothesis based on bootstrapping and the probability
> > > distribution for a separability measure.
>
> > > However, as a practical engineer, I can live with
> > > comparing overlaps of mean +/- 2*stdv confidence
> > > intervals for MSE estimates obtained from 10-fold XVAL.
>
> I guess I should look up the F-test and see how bad I am.

Saw this Bruce Weaver post in sci.stat.math:

Some authors suggest using Akaike's Information Criterion (AIC) or
one
of its competitors for comparing non-nested models. E.g., see
section
F in the GraphPad regression book (link below).

  http://www.graphpad.com/manuals/prism4/RegressionBook.pdf


Hope this helps.

Greg