Re: [R] 'asymmetric span' for 2D loess?

From: Tokuyasu, Taku <>
Date: Tue, 03 Jun 2008 09:48:18 -0700

Dear Prof Ripley,

> > Hello,
> >
> > I am interested in performing a 2D loess smooth on microarray data, i.e.
> > log2 ratios on a 2D grid, using different spans in the horizontal and
> > vertical directions (the immediate reason being that replicate spots are
> > laid out in the horizontal direction). Is it possible to do this in R?
> > Functions like loess(stats) seem to apply the same span for all
> > predictors, which carries over to functions like ma2D(marray).
> See the next comment. 'span' applies to 2D distances, and I think you
> need to rescale your inputs so Euclidean distance is appropriate.

That's a great idea.

> > As an elementary second question, are there circumstances where one
> > expects to see a substantial difference in the fits between say loess(y
> > ~ x1 + x2) and loess(y ~ x1 * x2) with an interaction term (and if so,
> > what are they)?
> From the help page:
> formula: a formula specifying the numeric response and one to four
> numeric predictors (best specified via an interaction, but
> can also be specified additively). Will be coerced to a
> formula if necessary.
> So the two versions both specify smoothing in 2D.
> You can use things like lo(x1) + lo(x2) in some gam fits.

Hadn't thought of that, I will explore this.

> It often helps to read the primary sources, in this case chapters in the
> White Book (Chambers & Hastie, nominally 1992, actually published in
> 1991).
> --
> Brian D. Ripley,
> Professor of Applied Statistics,
> University of Oxford, Tel: +44 1865 272861 (self)
> 1 South Parks Road, +44 1865 272866 (PA)
> Oxford OX1 3TG, UK Fax: +44 1865 272595

Thanks very much for the help. Nice photos on the Web, by the way.



Taku A. Tokuyasu, PhD
UCSF Helen Diller Family Comprehensive Cancer Center San Francisco, CA 94143-0808 mailing list PLEASE do read the posting guide and provide commented, minimal, self-contained, reproducible code. Received on Tue 03 Jun 2008 - 17:59:49 GMT

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