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RE: st: RE: Quantile regression runtimes


From   "Martin Weiss" <martin.weiss1@gmx.de>
To   <statalist@hsphsun2.harvard.edu>
Subject   RE: st: RE: Quantile regression runtimes
Date   Sat, 5 Jun 2010 22:11:47 +0200

<>

So, for anyone who wants to replicate Jacob`s problem:


***********
vers 11.1

clear*
set mem 1G
set obs 673721

gen x1= rnormal()
gen x2= runiform() 
gen x3=rchi2(3)

gen y=1*2*x1-3*x2+2*x3+rnormal()

timer clear
forv q=1/9{
	timer on `q' 
	qreg y x?, q(`=`q'/10')
	timer off `q'
}

timer list
**********

I end up with a -remarkably- U-shaped list of times:



. timer list
   1:     24.24 /        1 =      24.2400
   2:     18.06 /        1 =      18.0600
   3:     13.92 /        1 =      13.9200
   4:      8.20 /        1 =       8.2000
   5:      5.24 /        1 =       5.2400
   6:      9.40 /        1 =       9.4000
   7:     14.46 /        1 =      14.4600
   8:     19.04 /        1 =      19.0400
   9:     29.87 /        1 =      29.8700


This may have much to do with my setup of the problem. How many covariates
are there in your -qreg- model, Jacob?


HTH
Martin


-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Jacob Felson
Sent: Samstag, 5. Juni 2010 21:50
To: statalist@hsphsun2.harvard.edu
Subject: Re: st: RE: Quantile regression runtimes

Martin,

Sorry I was vague.  The analytical sample was 673,721.

Jacob Felson



On Sat, Jun 5, 2010 at 3:28 PM, Martin Weiss <martin.weiss1@gmx.de> wrote:
>
> <>
>
> " on a very
> large dataset (the Census' 2008 American Community Survey 1% samples)."
>
>
> How large is the dataset exactly, Jacob? Remember, you cannot presume
every
> listmember is familiar with this dataset, even though in your profession
it
> may well be famous...
>
>
> HTH
> Martin
>
> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu
> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Jacob Felson
> Sent: Samstag, 5. Juni 2010 21:04
> To: statalist@hsphsun2.harvard.edu
> Subject: st: Quantile regression runtimes
>
> I'm curious about the runtimes for quantile regression.  I am running
> decile regressions (.1, .2, .3, .4, .5, .6, .7, .8, and .9) on a very
> large dataset (the Census' 2008 American Community Survey 1% samples).
>  Runtimes generally decrease as deciles increase:
>
>
> Runtimes are in minutes
>
> .1    74.27413
> .2   34.95253
> .3     13.1072
> .4    8.738133
> .5    8.738133
> .6   4.369067
> .7     6.5536
> .8    8.738133
>
>
> I'm very curious -- why is the runtime for .1 regression so much
> higher than for .2?  And what might explain the general pattern of
> these runtimes?
>
>
> Thanks,
>
> Jacob Felson
> Assistant Professor
> Department of Sociology
> William Paterson University
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