[R] partially linear models
Liaw, Andy
andy_liaw at merck.com
Tue Dec 20 22:39:06 CET 2005
From: Peter Dalgaard
>
> "Liaw, Andy" <andy_liaw at merck.com> writes:
>
> > This doesn't look like an R question, as I know of no pre-packaged
> > functionality publicly available that can fit the model
> that Elizabeth
> > described, and it doesn't seem like she's particularly
> interested in an
> > R-based answer, either.
> >
> > My gut feeling is that if there is a test of significance
> for beta in such a
> > model, it probably shouldn't depend upon how f() is fitted,
> wavelets or
> > otherwise. I.e., any test for the linear component in a
> partially linear
> > model ought to do just fine. The main difference here,
> from a fully linear
> > model, is that one no longer can estimate E(y) without
> bias, even with the
> > assumption that the model is correct. What gets messier still is if
> > data-dependent smoothing/de-noising is done in estimating
> f(), as that opens
> > up a whole bucket of nasty creatures.
> >
> > I could be off, though, so take this with a truck-load of NaCl...
>
> Isn't it just a gam() model (package mgcv), if you replace the
> wavelets with splines?
I believe so.
> I haven't messed with this for a decade, but I seem to recall that
> there's a result to the effect that you need to undersmooth f slightly
> to get optimal inference for the beta. Perhaps look in Green &
> Silverman for the reference.
A quote I heard from Prof. David Ruppert: "There are lies, damned lies, and
then big O notations."
I presume the need to undersmooth is to reduce the bias of the `smooth'.
The problem is, by how much should one undersmooth, so the bias would go
from O(k*n^-4) to O(k*n^-5) (I'm just making this up, but you get the idea)?
Cheers,
Andy
>
> > Andy
> >
> > From: Spencer Graves
> > >
> > > I have seen no replies to this post, and I don't know
> > > that I can
> > > help, either. However, I wonder if you tried
> "RSiteSearch" with your
> > > favorite key words and phrases? For example, I just got
> 107 hits for
> > > 'RSiteSearch("wavelets")'. I wonder if any of them might
> help you.
> > >
> > > If you'd like further help from this list, please
> > > submit another
> > > post. However, before you do, I suggest you read the
> posting guide!
> > > "www.R-project.org/posting-guide.html". Anecdotal
> evidence suggests
> > > that posts more consistent with the guide tend to receive
> > > quicker, more
> > > useful replies.
> > >
> > > Best Wishes,
> > > spencer graves
> > >
> > > Elizabeth Lawson wrote:
> > >
> > > > Hey,
> > > >
> > > > I am estiamting a partially linear model
> > > y=X\beta+f(\theta) where the f(\theta) is estiamted using
> wavelets.
> > > >
> > > > Has anyone heard of methods to test if the betas are
> > > significant or to address model fit?
> > > >
> > > > Thanks for any thoughts or comments.
> > > >
> > > > Elizabeth Lawson
> > > >
> > > > __________________________________________________
> > > >
> > > >
> > > >
> > > > [[alternative HTML version deleted]]
> > > >
> > > > ______________________________________________
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> > >
> > > --
> > > Spencer
> > > Graves, PhD
> > > Senior Development Engineer
> > > PDF Solutions, Inc.
> > > 333 West San Carlos Street Suite 700
> > > San Jose, CA 95110, USA
> > >
> > > spencer.graves at pdf.com
> > > www.pdf.com <http://www.pdf.com>
> > > Tel: 408-938-4420
> > > Fax: 408-280-7915
> > >
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> >
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> >
>
> --
> O__
> ---- Peter Dalgaard Øster Farimagsgade 5, Entr.B
> c/ /'_ --- Dept. of Biostatistics PO Box 2099, 1014 Cph. K
> (*) \(*) -- University of Copenhagen Denmark Ph:
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