I'm CC'ing this to the R-SIG-robust mailing list
[R Special Interest Group on robust statistics]
so it's properly archived there as well.
Follow up ideally should only go there.
{BTW: Did you know that to *search* mailing list archives of
such R-SIG-foo mailing lists, you can use google very
efficiently by prepending the mailing list name and 'site:stat.ethz.ch'?
e.g., use google search on
"R-SIG-robust site:stat.ethz.ch lmrob"
}
>>>>> "BertG" == Berton Gunter <[EMAIL PROTECTED]>
>>>>> on Thu, 22 Jun 2006 09:44:33 -0700 writes:
BertG> Many thanks for this Martin. There now are several
BertG> packages with what appear to be overlapping functions
BertG> (or at least algorithms). Besides those you
BertG> mentioned, "robust" and "roblm" are at least two others.
actually quite particular ones:
- "roblm" by Matias Salibian-Barreras is really predecessor to
parts in 'robustbase'. His roblm() function is now lmrob() in
robustbase, i.e., robustbase::lmrob(), and lmrob() is a bit
more efficient and further has a anova() method.
- "robust" : by Kjell Konis -- is planned to become a full port
of the S-plus library section "robust" (from
Insightful, also mainly by Kjell Konis, built
on code of many more, see DESCRIPTION).
At the moment it comes with a 'Insightful Robust Library License'
which seems a kind of open source licence, but pretty "peculiar"
(to me: IANAL (I am not a lawyer)).
At the moment it only has "robust covariance + location", but
when it will contain everything from its S-plus counterpart,
it will be a very nice benchmark; in many parts "first rate".
BertG> Any recommendations about how or whether to
BertG> choose among these for us enthusiastic but non-expert
BertG> users?
As I said (in reply to Andy's suggestion) there will be a CRAN
task view "real soon now"
in order to give some guidance on the diverse packages with
robustness functionality.
BertG> Cheers, Bert
>> -----Original Message----- From: Martin Maechler
>> [mailto:[EMAIL PROTECTED] Sent: Thursday, June
>> 22, 2006 2:04 AM To: Berton Gunter Cc: 'Robert Powell';
>> r-help@stat.math.ethz.ch Subject: Re: [R] Rosner's test
>>
>> >>>>> "BertG" == Berton Gunter <[EMAIL PROTECTED]>
>> >>>>> on Tue, 13 Jun 2006 14:34:48 -0700 writes:
>>
BertG> RSiteSearch('Rosner') ?RSiteSearch or search directly
BertG> from CRAN.
>>
BertG> Incidentally, I'll repeat what I've said
BertG> before. Don't do outlier tests. They're
BertG> dangerous. Use robust methods instead.
>> Yes, yes, yes!!!
>>
>> Note that rlm() or cov.rob() from recommended package
>> MASS will most probably be sufficient for your needs.
>>
>> For slightly newer methodology, look at package
>> 'robustbase', or also 'rrcov'.
>>
>> Martin Maechler, ETH Zurich
>>
BertG> -- Bert Gunter Genentech Non-Clinical Statistics
BertG> South San Francisco, CA
>>
BertG> "The business of the statistician is to catalyze the
BertG> scientific learning process." - George E. P. Box
>>
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