From thomas@biostat.washington.edu  Thu Oct 14 16:36:17 1999
From: thomas@biostat.washington.edu (Thomas Lumley)
Date: Thu, 14 Oct 1999 08:36:17 -0700 (PDT)
Subject: [R] Regression on non linear model
In-Reply-To: <199910140700.RAA23011@snowy.nsw.cmis.CSIRO.AU>
Message-ID: <Pine.GSO.4.10.9910140833150.2421-100000@wompom.biostat.washington.edu>

On Thu, 14 Oct 1999, Bill Venables wrote:

> One further advantage of doing it this way (in S-PLUS at least) is that you can
> plot that component of the fitted curve very simply using plot.gam.  Now I know
> we don't have a gam() in R yet, but I hope we plan to do so sometime and my
> suggestion would be to start with a plot.gam and release that first.  It could
> be done in a wet weekend (but I regret to say the weekends here are simply
> beautiful.... :-)

I have a predict(, type="terms") and also resid(,type="partial") for glms
which are the main part of these plots. I wrote it a few versions ago, so
I will probably have to update a bit. 

	-thomas


Thomas Lumley
Assistant Professor, Biostatistics
University of Washington, Seattle

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[R] Regression on non linear model
Thomas Lumley