On 1 Mar 2002 00:36:01 -0800, [EMAIL PROTECTED] (Alex Yu)
wrote:
I know that robust regression can downweight outliers. Should someone
apply robust regression when the data have skewed distributions but do not
have outliers? Regression assumptions require normality of residuals
If, for example, normality assumption holds then by doing robust
regression instead of OLS you lose efficiency. So, it's not the same
result after all. But you can do both, compare and decide. If robust
regression produces results which are not really different from the OLS
then stay with OLS
I know that robust regression can downweight outliers Should someone
apply robust regression when the data have skewed distributions but do not
have outliers? Regression assumptions require normality of residuals, but
not the normality of raw scores So does it help at all to use robust
= Original Message From Michael Joner [EMAIL PROTECTED] =
Does it make a big difference if I use
an MM regression, or LTS, or LMS?
Good question.
I answered your first post from a basic, introductory level. I was trying to
convey the idea of robust regression. I used LMS as my
At 04:00 PM 1/9/02 -0700, Michael Joner wrote:
Hi,
Can anyone explain on the group or point me to an appropriate website
or
book which discusses robust regression? Particularly I'm interested
in
the differences between the MM and LTS robust regressions and a
simple
linear regression. What
Hi Humberto,
You have given an excellent simplified account of the usefulness of
robust regression and followed it by whole hearted support for Excel uses
in Statistics. It looks like you belong to a delta (in mathematical sense)
group. Anyway, what do you think about the credibility of Excel
Thanks for all the information. Do you know anything about the other
variations of robust regression? Does it make a big difference if I use
an MM regression, or LTS, or LMS?
Mike
On 11 Jan 2002 11:07:59 -0800 [EMAIL PROTECTED] (Humberto Barreto)
wrote:
A book:
Rousseeuw, P.J., and Leroy
Hi,
Does someone know how to include weights in the S-Plus rdl1.s algorithm
(the robust regression algorithm developed by Hubert Rousseeuw)? Of
course, the algorithm already include a weighting scheme (based on
distances of x points w.r.t. a robust center of an ellipsoid) but I
want, before
