Re: OT Quantile Regression Why not ranks or percentiles?
Posted by
Jon K Peck on
Oct 16, 2013; 5:59pm
URL: http://spssx-discussion.165.s1.nabble.com/OT-Quantile-Regression-Why-not-ranks-or-percentiles-tp5722584p5722592.html
Quantile regression builds models of the
specified quantiles in the same way as ordinary regression builds models
of means, except that they are computationally much more complex. I
doubt that anyone would want to build models of, say, every quantile in
(0,1) by .1. If you are interested in how the coefficients vary by
quantile, a half dozen or so points should give a pretty good picture.
Jon Peck (no "h") aka Kim
Senior Software Engineer, IBM
[hidden email]
phone: 720-342-5621
From:
Art Kendall <[hidden email]>
To:
[hidden email],
Date:
10/16/2013 11:48 AM
Subject:
[SPSSX-L] OT
Quantile Regression Why not ranks or percentiles?
Sent by:
"SPSSX(r)
Discussion" <[hidden email]>
Just curious.
As a general rule of thumb one wants a variable to
be as fine grained as is practical in the situation.
However, the few examples I have seen of quantile regression have coarsened
to 5 or so values.
Is there a substantive or computational reason for using this few
values?
--
Art Kendall
Social Research Consultants
Art Kendall
Social Research Consultants
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Quantile Regression Why not ranks or percentiles?
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