[R] Fitting data and removing outliers

[stephen sefick]

Do you have a good reason to throw these points out?

On Fri, Jul 13, 2012 at 2:17 PM, David L Carlson <dcarlson at tamu.edu> wrote:
> I didn't actually see any question in this posting, but instead of removing the outliers consider using a robust linear model.
>
> library(MASS)
> ?rlm
>
> The TeachingDemos package has a data set called outliers to show what can happen when you iteratively remove "outliers" in the way you suggest.
>
> -------------------------------------
> David L Carlson
> Associate Professor of Anthropology
> Texas A&M University
> College Station, TX 77840-4352
>
>
> ----- Original Message -----
>
> From: "Lauren Vogric" <lvogric at grahamcapital.com>
> To: r-help at r-project.org
> Sent: Friday, July 13, 2012 1:36:43 PM
> Subject: [R] Fitting data and removing outliers
>
> What I'm trying to do is create best fit line in R for a set of data points and then remove all the outliers to re-create a best fit. I can't use IQR because the outliers I have in mind are easily within the range, but way out of line for the best fit, which is ruining the fit. I'd rather throw out those points all together.
>
> Thanks!
>
> [[alternative HTML version deleted]]
>
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-- 
Stephen Sefick
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Auburn University
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