Message-ID: <4EFE42AD.108@paulhurley.co.uk>
Date: 2011-12-30T23:01:01Z
From: Paul Bivand
Subject: good method of removing outliers?
In-Reply-To: <CAPNjSFad447-trBfEhYR5uZ4Z6kh4K8Mg60eNeeakPh0C0Bgqg@mail.gmail.com>
On 30/12/11 17:03, Michael wrote:
> Happy holidays all!
>
> I know it's very subjective to determine whether some data is outlier or
> not...
>
> But are there reasonally good and realistic methods of identifying outliers
> in R?
>
> Thanks a lot!
>
>
Ignoring the moral questions for a moment (totaly depends on your
defintion of an outlier, your dataset, it's distribution etc etc), for
the technical implementation, try the outliers package
(http://www.stats.bris.ac.uk/R/web/packages/outliers/index.html), which
implements the Grubbs and Cox tests. Also, see this stackoverflow
answer of mine that shows an implementation of the Llund test for
outliers within a regression ( http://stackoverflow.com/a/1444548/74658 ).
Regards,
Paul.