[RsR] best robust fit

[Pep Serra]

I am not an expert, but I think AIC is not suitable when using robust 
statistics, maybe someone smarter may give a hint on this
I checked

http://www.mail-archive.com/r-help@stat.math.ethz.ch/msg39949.html

Thank you anyways and please do not hesitate to respond if you have 
further comments...

pep
Al 01/12/2010 15:51, En/na Samuel Le ha escrit:
> Have you thought of the Akaike Information Criterion? It is the R squared penalized by the number of regressors. You can access to it using reg$AIC if reg is your regression object.
>
> Samuel
>
> -----Original Message-----
> From: r-sig-robust-bounces using r-project.org [mailto:r-sig-robust-bounces using r-project.org] On Behalf Of Pep Serra
> Sent: 01 December 2010 14:48
> To: r-sig-robust using r-project.org
> Subject: [RsR] best robust fit
>
>
> dear all,
>
> I want to choose between different polynomial robust  regressions, however R2 may be misleading since the highest de degree is, the "better fit" to data. Is there any function implemented in robust or robustbase that computes an index for "model selection" ???
>
> Thanx for helping!
> pep
>
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