[R] Non-normal residuals.

[Ravi Varadhan]

There is also the tlm() function in "hett" package for fitting linear models
under t-distributed, heteroscedastic errors.

Ravi.

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Ravi Varadhan, Ph.D.

Assistant Professor, The Center on Aging and Health

Division of Geriatric Medicine and Gerontology 

Johns Hopkins University

Ph: (410) 502-2619

Fax: (410) 614-9625

Email: rvaradhan at jhmi.edu

Webpage:
http://www.jhsph.edu/agingandhealth/People/Faculty_personal_pages/Varadhan.h
tml

 

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-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] On
Behalf Of David Scott
Sent: Wednesday, October 28, 2009 6:26 AM
To: Karl Ove Hufthammer
Cc: r-help at stat.math.ethz.ch
Subject: Re: [R] Non-normal residuals.

Karl Ove Hufthammer wrote:
> On Tue, 27 Oct 2009 18:06:02 -0400 Ben Bolker <bolker at ufl.edu> wrote:
>>   If transforming your data brings you closer to satisfying
>> the assumptions of your analytic methods and having a sensible
>> analysis, then that's good.  If it makes things worse, that's bad.
>> Other choices, depending on the situation, include robust methods
>> (for "outlier" problems); generalized linear models etc. (for
>> discrete data from standard distributions); models using t- instead
>> of normally distributed residuals;
> 
> I have sometimes wondered about this: Which functions/packages do you 
> use to fit a (perhaps just a simple linear) model with t-distributed 
> residuals (or residuals of a different distribution)?
> 
Package sn has this facility I believe.

David Scott

-- 
_________________________________________________________________
David Scott	Department of Statistics
		The University of Auckland, PB 92019
		Auckland 1142,    NEW ZEALAND
Phone: +64 9 923 5055, or +64 9 373 7599 ext 85055
Email:	d.scott at auckland.ac.nz,  Fax: +64 9 373 7018

Director of Consulting, Department of Statistics

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