Martin, Kate, Fernando, et al.
Be careful bootstrapping robust estimators. The trouble is that when resampling
is done with replacement, the outliers can be selected too many times which
would ruin the standard error estimates. Martin is right that bootstrapping
would be fine if there are not too many outliers. Otherwise, Jackknifing will
likely work better, especially if you use a delete more than one version. For a
zero weight for outliers M estimator, a high breakdown starting value like
least trimmed squares would be a good idea.
arny
Arnold J. Stromberg
Professor and Chair
Department of Statistics
University of Kentucky
817 Patterson Office Tower
Lexington, KY 40506-0027
Phone: 859-257-6115
Fax: 859-323-1973
________________________________________
From: [EMAIL PROTECTED] [EMAIL PROTECTED] On Behalf Of Martin Maechler [EMAIL
PROTECTED]
Sent: Saturday, May 10, 2008 5:07 AM
To: Katharine Mullen; elnano
Cc: r-help@r-project.org; [EMAIL PROTECTED]
Subject: Re: [RsR] [R] function in nls argument -- robust estimation
Hi Kate and Fernando,
I'm late into this thread,
but from reading it I get the impression that Fernando really
wants to do *robust* (as opposed to least-squares) non-linear
model fitting. His proposal to set residuals to zero when they
are outside a given bound is a very special case of an
M-estimator, namely (if I'm not mistaken) the so-called "Huber
skipped-mean", an M-estimator with psi-function
psi <- function(x, k) ifelse(abs(x) <= k, x, 0)
It is known that this can be far from optimal, and either using
Huber-psi or "a redescender" such as Tukey's biweight can be
considerably better.
Also note that the standard inference (std.errors, P-values, ...)
that you'd get from summary(nlsfit) or anova(nls1, nl2) is
*invalid* here, since you are effectively using *random* weighting.
The nlrob() function in package 'robustbase'
implements M-estimation of nonlinear models directly.
Unfortunately, how to do correct inference in this situation
is a hard problem, probably even an open research question in
parts. I would expect that "the" bootstrap should work if you only
have a few outliers.
I don't have time at the moment to look at the example data and
the model, and show you how to use it for nlrob();
if you find a way to you it for nls() , then the same should
work for nlrob().
I'm CCing this to the specialists for "Robust Stats with R"
mailing list, R-SIG-robust.
Best regards,
Martin Maechler
ETH Zurich
>>>>> "KateM" == Katharine Mullen <[EMAIL PROTECTED]>
>>>>> on Fri, 9 May 2008 15:50:08 +0200 (CEST) writes:
KateM> You can take minpack.lm_1.1-0 (source code and MS Windows build,
KateM> respectively) from here:
KateM> http://www.nat.vu.nl/~kate/minpack.lm_1.1-0.tar.gz
KateM> http://www.nat.vu.nl/~kate/minpack.lm_1.1-0.zip
KateM> The bug that occurs when nprint = 0 is fixed. Also fixed is another
KateM> problem suggested your example: when the argument par is a list,
calling
KateM> summary on the output of nls.lm was not working.
KateM> I'll submit the new version to CRAN soon.
KateM> This disscusion has been fruitful - thanks for it.
KateM> On Fri, 9 May 2008, Katharine Mullen wrote:
>> You indeed found a bug. I can reproduce it (which I should have tried to
>> do on other examples in the first place!). Thanks for finding it.
>>
>> It will be fixed in version 1.1-0 which I will submit to CRAN soon.
>>
>> On Fri, 9 May 2008, elnano wrote:
>>
>> >
>> > Find the data (data_nls.lm_moyano.txt) here:
>> > ftp://ftp.bgc-jena.mpg.de/pub/outgoing/fmoyano
>> >
>> >
>> >
>> > Katharine Mullen wrote:
>> > >
>> > > Thanks for the details - it sounds like a bug. You can either send
me the
>> > > data in an email off-list or make it available on-line somewhere, so
that
>> > > I and other people can download it.
>> > >
>> > >
>> > > ______________________________________________
>> > > R-help@r-project.org mailing list
>> > > https://stat.ethz.ch/mailman/listinfo/r-help
>> > > PLEASE do read the posting guide
>> > > http://www.R-project.org/posting-guide.html
>> > > and provide commented, minimal, self-contained, reproducible code.
>> > >
>> > >
>> >
>> > --
>> > View this message in context:
http://www.nabble.com/function-in-nls-argument-tp17108100p17146812.html
>> > Sent from the R help mailing list archive at Nabble.com.
>> >
>> > ______________________________________________
>> > R-help@r-project.org mailing list
>> > https://stat.ethz.ch/mailman/listinfo/r-help
>> > PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
>> > and provide commented, minimal, self-contained, reproducible code.
>> >
>>
>> ______________________________________________
>> R-help@r-project.org mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>>
KateM> ______________________________________________
KateM> R-help@r-project.org mailing list
KateM> https://stat.ethz.ch/mailman/listinfo/r-help
KateM> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
KateM> and provide commented, minimal, self-contained, reproducible code.
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