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From |
"Martin Weiss" <martin.weiss1@gmx.de> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
RE: st: RE: Quantile regression runtimes |

Date |
Sat, 5 Jun 2010 22:38:24 +0200 |

<> So, Jacob, I bet the answer is somewhere in the "Methods and Formulas" section in [R], page 1463. It mentions, for instance, that for the median, there is no need to weight observations, so that would be consistent with my observation of the lowest timing for the 50% quantile. I am not enough of an expert on this subject, but the function being optimized in the iterations for -qreg-, in conjunction with the idiosyncracies of your data, must hold the key to this riddle. HTH Martin -----Original Message----- From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Martin Weiss Sent: Samstag, 5. Juni 2010 22:20 To: statalist@hsphsun2.harvard.edu Subject: RE: st: RE: Quantile regression runtimes <> The -set mem 1G- line, of course, is not necessary. It is a remnant from a couple of minutes ago, when I imagined Jacob`s sample to be much, much bigger... HTH Martin -----Original Message----- From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Martin Weiss Sent: Samstag, 5. Juni 2010 22:12 To: statalist@hsphsun2.harvard.edu Subject: RE: st: RE: Quantile regression runtimes <> 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 > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ > > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ > * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**st: Quantile regression runtimes***From:*Jacob Felson <felsonj@gmail.com>

**Re: st: RE: Quantile regression runtimes***From:*Jacob Felson <felsonj@gmail.com>

**RE: st: RE: Quantile regression runtimes***From:*"Martin Weiss" <martin.weiss1@gmx.de>

**RE: st: RE: Quantile regression runtimes***From:*"Martin Weiss" <martin.weiss1@gmx.de>

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