[R] Robust regression for ordered data
Jeff Newmiller
jdnewmil at dcn.davis.ca.us
Mon Oct 8 01:41:03 CEST 2012
I don't know about the topic of your question. Have you used the RSiteSearch function to research it yourself?
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Sent from my phone. Please excuse my brevity.
Eiko Fried <torvon at 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 <jdnewmil at 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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>> Jeff Newmiller The ..... ..... Go
>Live...
>> DCN:<jdnewmil at dcn.davis.ca.us> Basics: ##.#. ##.#. Live
>> Go...
>> Live: OO#.. Dead: OO#..
>Playing
>> Research Engineer (Solar/Batteries O.O#. #.O#. with
>> /Software/Embedded Controllers) .OO#. .OO#.
>rocks...1k
>>
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>> Sent from my phone. Please excuse my brevity.
>>
>> Eiko Fried <torvon at 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
>> >
>> > [[alternative HTML version deleted]]
>> >
>> >______________________________________________
>> >R-help at 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.
>>
>>
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