On 08/10/2012 00:37, Bert Gunter wrote:
Have you checked the Robust task view on CRAN?? Would seem that that
should have been the first place to look.
It is still a conceptual question. I presume this means an ordered
response, and then we need to know what is meant by 'regression'.
If you tell us precisely what robust method you want to know about, you
may get help about whether it is available in R. But I surmise that
you need rather to be looking at ordinal regression (polr in MASS, for
example), and you will not find that in the 'Robust' task view. In the
task view, 'robust' is a technical term and I don't think 'Elko Fried'
is using it in the sense the author of the task view is.
-- Bert
On Sun, Oct 7, 2012 at 3:30 PM, Eiko Fried <tor...@gmail.com> wrote:
Thank you Jeff! Please ignore the first of my two questions then, and
apologies for not making it clear that my second question was about R.
(2) "Are there ways of using robust regressions with ordered data" ... in
R?
Thank you
On 7 October 2012 18:26, Jeff Newmiller <jdnew...@dcn.davis.ca.us> wrote:
This does not appear to be a question about R. You should post in a list
or forum dedicated to discussing statistics theory, such as
stats.stackoverflow.com.
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Eiko Fried <tor...@gmail.com> wrote:
I have two regressions to perform - one with a metric DV (-3 to 3), the
other with an ordered DV (0,1,2,3).
Neither normal distribution not homoscedasticity is given. I have a two
questions:
(1) Some sources say robust regression take care of both lack of normal
distribution and heteroscedasticity, while others say only of normal
distribution. What is true?
(2) Are there ways of using robust regressions with ordered data, or is
that only possible for metric DVs?
Thanks
Torvon
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--
Brian D. Ripley, rip...@stats.ox.ac.uk
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
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Oxford OX1 3TG, UK Fax: +44 1865 272595
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