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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 22:11:47 +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 > * > * 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/

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

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

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

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