[R] How to get around heteroscedasticity with non-linear leas t squares in R?

Quin Wills quin.wills at googlemail.com
Wed Feb 22 04:19:06 CET 2006


Thank you all, this has been a great help (including the methodological
advice). Very interesting - I'll be sure to read the lecture.

Quin

-----Original Message-----
From: Liaw, Andy [mailto:andy_liaw at merck.com] 
Sent: 22 February 2006 01:18
To: 'Brian S Cade'; KjetilBrinchmannHalvorsen at gmail.com
Cc: Quin Wills; r-help at stat.math.ethz.ch; r-help-bounces at stat.math.ethz.ch
Subject: RE: [R] How to get around heteroscedasticity with non-linear leas t
squares in R?

From: Brian S Cade
> 
> Instead of thinking that the heteroscedasticity is a nuisance and 
> something to "get around", i.e, just wanting weighted 
> estimates of the 
> mean function, you might want to think about what 
> heteroscedasticity is 
> telling you and estimate some other quantities.  

Indeed!  See Prof. Carroll's 2002 Fisher Lecture:
http://www.stat.tamu.edu/ftp/pub/rjcarroll/2003.papers.directory/published_F
isher_Lecture.pdf
(There's Powerpoint file on his web page, too.)

Andy

> Heteroscedasticity is 
> telling you that the conditional distributions don't change 
> at a constant 
> rate across all portions of the distribution (think 
> percentiles or more 
> generally quantiles) and, therefore, a function for the mean 
> (no matter 
> how precisely estimated) cannot tell you all there is to know 
> about your 
> dose-response relation.  Why not go after estimating the conditional 
> quantile functions directly with nonlinear quantile 
> regression, function 
> nlrq() in the quantreg package? 
> 
> Brian
> 
> Brian S. Cade
> 
> U. S. Geological Survey
> Fort Collins Science Center
> 2150 Centre Ave., Bldg. C
> Fort Collins, CO  80526-8818
> 
> email:  brian_cade at usgs.gov
> tel:  970 226-9326
> 
> 
> 
> Kjetil Brinchmann Halvorsen <kjetilbrinchmannhalvorsen at gmail.com> 
> Sent by: r-help-bounces at stat.math.ethz.ch
> 02/21/2006 03:31 PM
> Please respond to
> KjetilBrinchmannHalvorsen at gmail.com
> 
> 
> To
> Quin Wills <quin.wills at googlemail.com>
> cc
> r-help at stat.math.ethz.ch
> Subject
> Re: [R] How to get around heteroscedasticity with non-linear 
> least squares 
> in R?
> 
> 
> 
> 
> 
> 
> Quin Wills wrote:
> > I am using "nls" to fit dose-response curves but am not sure how to 
> approach
> > more robust regression in R to get around the problem of 
> the my error
> > showing increased variance with increasing dose. 
> > 
> 
> package "sfsmisc"  has rnls (robust nls)
> which might be of use.
> 
> Kjetil
> 
> > 
> > 
> > My understanding is that "rlm" or "lqs" would not be a good 
> idea here.
> > 'Fairly new to regression work, so apologies if I'm missing 
> something
> > obvious.
> > 
> > 
> > 
> > 
> >                [[alternative HTML version deleted]]
> > 
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