They are due to measurement error, sample of a different population, or
... ? What is the unusual event? Does it explain something important
about the system that you are working on? I am not telling you not to
do what you are doing, but just writing things that I consider when I am
doing regression modelling.
FWIW,
Stephen
On 07/13/2012 02:26 PM, Lauren Vogric wrote:
Yes, they are unusual events that occurred that affected my data. They have no
positive affect in shaping a strong model.
-----Original Message-----
From: stephen sefick [mailto:ssef...@gmail.com]
Sent: Friday, July 13, 2012 3:24 PM
To: David L Carlson
Cc: Lauren Vogric; r-help@r-project.org
Subject: Re: [R] Fitting data and removing outliers
Do you have a good reason to throw these points out?
On Fri, Jul 13, 2012 at 2:17 PM, David L Carlson <dcarl...@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" <lvog...@grahamcapital.com>
To: r-help@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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______________________________________________
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--
Stephen Sefick
**************************************************
Auburn University
Biological Sciences
331 Funchess Hall
Auburn, Alabama
36849
**************************************************
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Let's not spend our time and resources thinking about things that are so little
or so large that all they really do for us is puff us up and make us feel like
gods. We are mammals, and have not exhausted the annoying little problems of
being mammals.
-K. Mullis
"A big computer, a complex algorithm and a long time does not equal science."
-Robert Gentleman
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