Hi Laura, The fact that you had copied Prof. Ripley's response suggested to me that this was so. Nevertheless, I think Martin Maechler was wise to emphasize the problem, just in case.
Bye, Mark. Laura POggio wrote: > > I am aware of the limits of the parameter R^2 in this case. However often > it > is required for many different reasons. And it is helpful to have a > function > that does it. The most important is to know the drawback of the"number", I > think. > > Laura > > > 2008/11/13 Martin Maechler <[EMAIL PROTECTED]> > >> >>>>> "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/> >> >> <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. >> > > [[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-tp20478161p20485534.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.
