Thanks for the details, I suspected something like that.
I think that begs the question: what is the meaning of quantile regression
through the origin? If the tau=.5 line does not pass through 1/2 the data
how do I interpret the line?
On Tue, Oct 6, 2015 at 8:03 AM, Roger Koenker <rkoenker at illinois.edu>
wrote:
>
> > On Oct 6, 2015, at 7:58 AM, Lorenz, David <lorenz at usgs.gov>
wrote:
> >
> > Did you verify that the correct percentages were above/below the
> regression
> > lines? I did a quick check and for example did not consistently get
50%
> of
> > the observed response values greater than the tau=.5 line. I did when
I
> > included the nonzero intercept term.
>
> Your "correct percentages" are only correct when you have an
intercept in
> the model,
> without an intercept there is no gradient condition to ensure that.
> >
> >
> >
> >> Date: Mon, 5 Oct 2015 21:14:04 +0530
> >> From: Preetam Pal <lordpreetam at gmail.com>
> >> To: stephen sefick <ssefick at gmail.com>
> >> Cc: "r-help at r-project.org" <r-help at
r-project.org>
> >> Subject: Re: [R] Quantile Regression without intercept
> >> Message-ID: <56129a41.025f440a.b1cf4.fffff5ee at
mx.google.com>
> >> Content-Type: text/plain; charset="UTF-8"
> >>
> >> Yes..it works. .... Thanks ??
> >>
> >> -----Original Message-----
> >> From: "stephen sefick" <ssefick at gmail.com>
> >> Sent: ?05-?10-?2015 09:01 PM
> >> To: "Preetam Pal" <lordpreetam at gmail.com>
> >> Cc: "r-help at r-project.org" <r-help at
r-project.org>
> >> Subject: Re: [R] Quantile Regression without intercept
> >>
> >> I have never used this, but does the formula interface work like
lm?
> Y~X-1?
> >>
> >>
> >> On Mon, Oct 5, 2015 at 10:27 AM, Preetam Pal <lordpreetam at
gmail.com>
> >> wrote:
> >>
> >> Hi guys,
> >>
> >> Can you instruct me please how to run quantile regression without
the
> >> intercept term? I only know about the rq function under quantreg
> package,
> >> but it automatically uses an intercept model. Icant change that,
it
> seems.
> >>
> >> I have numeric data on Y variable (Gdp) and 2 X variables (Hpa and
> >> Unemployment). Their sizes are 125 each.
> >>
> >> Appreciate your help with this.
> >>
> >> Regards,
> >> Preetam
> >> [[alternative HTML version deleted]]
> >>
> >> ______________________________________________
> >> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more,
see
> >> 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.
> >>
> >>
> >>
> >>
> >>
> >>
> >> --
> >>
> >> Stephen Sefick
> >> **************************************************
> >> Auburn University
> >> Biological Sciences
> >> 331 Funchess Hall
> >> Auburn, Alabama
> >> 36849
> >> **************************************************
> >> sas0025 at auburn.edu
> >> http://www.auburn.edu/~sas0025
> >> **************************************************
> >>
> >> Let's not spend our time and resources thinking about things
that are so
> >> little or so large that all they really do for us is puff us up
and
> make us
> >> feel like gods. We are mammals, and have not exhausted the
annoying
> little
> >> problems of being mammals.
> >>
> >> -K. Mullis
> >>
> >> "A big computer, a complex algorithm and a long time does not
equal
> >> science."
> >>
> >> -Robert Gentleman
> >> [[alternative HTML version deleted]]
> >>
> >>
> >>
> >>
> >
> > [[alternative HTML version deleted]]
> >
> > ______________________________________________
> > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> > 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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