[R] R-square in robust regression

[Mark Difford]

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 at 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 at 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]]
> 
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