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st: About filters for outliers


From   Kayla Bridge <kayla.bridge@outlook.com>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   st: About filters for outliers
Date   Thu, 13 Jun 2013 12:53:26 +0000

Thank you, Billy. Your suggestion is helpful.

Best,
Kayla

----------------------------------------
> Subject: Re: st: About filters for outliers
> From: william@williambuchanan.net
> Date: Mon, 10 Jun 2013 19:43:13 -0700
> To: statalist@hsphsun2.harvard.edu
>
> Why do you assume that the outliers are purely noise? There are several methods available to detect outliers which are well documented in the help file for regress. However, any program that would automatically drop these observations would have no way of know whether or not the observations were plausible or just problematic to the fit of the model. If you have many outliers I would suggest looking into alternative models that are robust to the specific context in which you are fitting your models.
>
> HTH,
> Billy
>
> Sent from my iPhone
>
> On Jun 10, 2013, at 19:35, Kayla Bridge <kayla.bridge@outlook.com> wrote:
>
>> Dear all,
>>
>> I am trying to rule out the noise in the data set, for example, the outliers. Is there any commands that can be used to achieve this target? Or what kind of filters can be used and how to apply in this situation? Any suggestion is appreciated.
>>
>> Best,
>> Kayla
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