Re: [R] R-square in robust regression

From: Mark Difford <mark_difford_at_yahoo.co.uk>
Date: Thu, 13 Nov 2008 02:36:46 -0800 (PST)

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 <ripley_at_stats.ox.ac.uk>
> Subject: Re: [R] R-square in robust regression
> To: PARKERSO <sophie.parker_at_vuw.ac.nz>
> Cc: r-help_at_r-project.org
> Message-ID:
> <alpine.LFD.2.00.0810200609590.21177@gannet.stats.ox.ac.uk>
> 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, ripley@stats.ox.ac.uk
> Professor of Applied Statistics,
> http://www.stats.ox.ac.uk/~ripley/<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_at_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_at_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.
Received on Thu 13 Nov 2008 - 10:40:05 GMT

Archive maintained by Robert King, hosted by the discipline of statistics at the University of Newcastle, Australia.
Archive generated by hypermail 2.2.0, at Thu 13 Nov 2008 - 11:30:24 GMT.

Mailing list information is available at https://stat.ethz.ch/mailman/listinfo/r-help. Please read the posting guide before posting to the list.

list of date sections of archive