>>>>> "LP" == Laura Poggio <[EMAIL PROTECTED]>
>>>>> on Thu, 13 Nov 2008 10:43:14 +0000 writes:
LP> yes thank you! it is perfect.
LP> I was using lmrob in package robustbase and it did not have that option
in
LP> the summary.
Yes....
lmRob() from "robust" is from a company which -- often being excellent --
has at times listened much more to its not-so-professional
customers instead of its expert advisors.
So, yes indeed, summary(lmRob(..)) happily reports
something like
"Multiple R-Squared: 0.620538" (number: for the stack loss example)
But the question is if the customer should get R^2 even in
casses where its definition is very doubtful and indeed
somewhat *counter* to the purpose of using methods that are NOT
least-squares based....
Martin Maechler, ETH Zurich
LP> 2008/11/13 Mark Difford <[EMAIL PROTECTED]>
>>
>> Hi Laura,
>>
>> >> I was searching for a way to compute robust R-square in R in order to
>> get
>> >> an
>> >> information similar to the "Proportion of variation in response(s)
>> >> explained
>> >> by model(s)" computed by S-Plus.
>>
>> There are several options. I have had good results using wle.lm() in
>> package
>> wle and lmRob() in package robust. The second option is perhaps closest
to
>> what you want.
>>
>> Regards, Mark.
>>
>>
>> Laura POggio wrote:
>> >
>> > I was searching for a way to compute robust R-square in R in order to
get
>> > an
>> > information similar to the "Proportion of variation in response(s)
>> > explained
>> > by model(s)" computed by S-Plus. This post is dealing with that. Would
be
>> > possible to have some hints on how to calculate this parameter within
R?
>> >
>> > Thank you very much in advance.
>> >
>> > Laura Poggio
>> >
>> >
>> >
>>
-----------------------------------------------------------------------------
>> > Date: Mon, 20 Oct 2008 06:15:49 +0100 (BST)
>> > From: Prof Brian Ripley <[EMAIL PROTECTED]>
>> > Subject: Re: [R] R-square in robust regression
>> > To: PARKERSO <[EMAIL PROTECTED]>
>> > Cc: r-help@r-project.org
>> > Message-ID:
>> > <[EMAIL PROTECTED]>
>> > Content-Type: TEXT/PLAIN; charset=US-ASCII; format=flowed
>> >
>> > On Sun, 19 Oct 2008, PARKERSO wrote:
>> >
>> >>
>> >> Hi there,
>> >> I have just started using the MASS package in R to run M-estimator
>> robust
>> >> regressions. The final output appears to only give coefficients,
degrees
>> > of
>> >> freedom and t-stats. Does anyone know why R doesn't compute R or
>> >> R-squared
>> >
>> > These as only valid for least-squares fits -- they will include the
>> > possible outliers in the measure of fit.
>> >
>> > And BTW, it is not 'R', but the uncredited author of the package who
made
>> > such design decisions.
>> >
>> >> and why doesn't give you any other indices of goodness of fit?
>> >
>> > Which ones did you have in mind? It does give a scale estimate of the
>> > residuals, and this determines the predition accuracy.
>> >
>> >> Does anyone know how to compute these in R?
>> >
>> > Yes.
>> >
>> >> Sophie
>> >
>> >
>> > --
>> > Brian D. Ripley, [EMAIL PROTECTED]
>> > Professor of Applied Statistics,
>> >
http://www.stats.ox.ac.uk/~ripley/<http://www.stats.ox.ac.uk/%7Eripley/>
>> <http://www.stats.ox.ac.uk/%7Eripley/>
>> > University of Oxford, Tel: +44 1865 272861 (self)
>> > 1 South Parks Road, +44 1865 272866 (PA)
>> > Oxford OX1 3TG, UK Fax: +44 1865 272595
>> >
>> > [[alternative HTML version deleted]]
>> >
>> > ______________________________________________
>> > 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/Re%3A-R-square-in-robust-regression-tp20478161p20478307.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.
>>
LP> [[alternative HTML version deleted]]
LP> ______________________________________________
LP> R-help@r-project.org mailing list
LP> https://stat.ethz.ch/mailman/listinfo/r-help
LP> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
LP> and provide commented, minimal, self-contained, reproducible code.
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