If not linear, then perhaps nlrob() in package robustbase. ------------------------------------- David L Carlson Associate Professor of Anthropology Texas A&M University College Station, TX 77840-4352
----- Original Message ----- From: "Stephen Sefick" <ssef...@gmail.com> To: "Lauren Vogric" <lvog...@grahamcapital.com>, r-help@r-project.org Sent: Friday, July 13, 2012 3:15:25 PM Subject: Re: [R] Fitting data and removing outliers 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]] >> >> ______________________________________________ >> R-help@r-project.org mailing list >> https://stat.ethz.ch/mailman/listinfo/r-help >> PLEASE do read the posting guide >> http://www.R-project.org/posting-guide.html >> and provide commented, minimal, self-contained, reproducible code. >> >> ______________________________________________ >> R-help@r-project.org mailing list >> https://stat.ethz.ch/mailman/listinfo/r-help >> PLEASE do read the posting guide >> http://www.R-project.org/posting-guide.html >> and provide commented, minimal, self-contained, reproducible code. > > > -- > Stephen Sefick > ************************************************** > Auburn University > Biological Sciences > 331 Funchess Hall > Auburn, Alabama > 36849 > ************************************************** > sas0...@auburn.edu > http://www.auburn.edu/~sas0025 > ************************************************** > > 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 ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
