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From |
"Keith Dear (home)" <[email protected]> |

To |
[email protected] |

Subject |
Re: st: AW: gllamm (poisson) execution time |

Date |
Fri, 26 Jun 2009 10:49:53 +1000 |

webuse ships, clear gen logserv=ln(service) glo X op_75_79 co_65_69 co_70_74 co_75_79 xtset ship

~~~~~~~~~ xtpoisson results ~~~~~~~~~ ------------------------------------------------------------------------------

-------------+----------------------------------------------------------------

logserv | (offset) -------------+----------------------------------------------------------------

-------------+----------------------------------------------------------------

------------------------------------------------------------------------------

~~~~~~~~~ gllamm results ~~~~~~~~~ ------------------------------------------------------------------------------

-------------+----------------------------------------------------------------

logserv | (offset)

----------------------------------------------------------------------------- ***level 2 (ship) var(1): .17662891 (.09378635) -----------------------------------------------------------------------------

Thanks Keith Jeph Herrin wrote:

If you have a single random effect, you may find -xtpoisson- is even faster than -xtmepoisson-. hth, Jeph Keith Dear (home) wrote:Ummm ... no (well, NOW I have).Except on the uni supercomputer, we only have Stata9, henceignorance. Time to upgrade!Many thanks Martin. Keith ps http://www.stata.com/help.cgi?xtmepoisson http://stata.com/stata10/mixedmodels.html Martin Weiss wrote:`<> Have you looked into -xtmepoisson-? HTH Martin -----Ursprüngliche Nachricht----- Von: [email protected] [mailto:[email protected]] Im Auftrag von Keith Dear (work) Gesendet: Mittwoch, 24. Juni 2009 08:01 An: [email protected] Cc: Ainslie Butler Betreff: st: gllamm (poisson) execution time`

We are trying to model daily mortality by poisson regression, over17 years, by postcode, with postcode as a single random intercept term.In Stata10/MP4 on a linux cluster our models each take 7 or 8 hoursto fit, which is too long to be feasible for exploratory analyses.The full dataset has >14 million rows of data: a row for every dayfor 1991-2007 for every postcode in Australia (~2200 postcodes), butto get things moving we are starting with smaller geographicalregions of only 100 or 200 postcodes. Thus N=17*365*(100 or 200),about a half or one million. Also we are starting with failrlysimple models, p=17 fixed-effect parameters just for trend andannual cycles. The models converge ok, eventually, in only a fewiterations and with typical condition number about 2.I found this in the list archives (from Sophia Rabe-Hesketh in 2003): ==> biggest gain is to reduce M, followed by n, p and NHere we have M=1, n=5 (down from the default of 8), p=17, but N=6E5or more. There does not seem to be much prospect of reducing any ofthose, indeed we will need to substantially increase p (for moreinteresting models) and N (to cover all of Australia at once).Is there hope? Are there alternatives to gllamm for this? Or are weoverlooking something basic here?Keith* * 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/

-- Dr Keith Dear Senior Fellow National Centre for Epidemiology and Population Health ANU College of Medicine, Biology and Environment Building 62, cnr Mills and Eggleston Roads Australian National University

T: 02 6125 4865 F: 02 6125 0740 M: 0424 450 396 W: nceph.anu.edu.au/Staff_Students/staff_pages/dear.php CRICOS provider #00120C http://canberragliding.org/ * * 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: Interpreting Poisson output***From:*"Data Analytics Corp." <[email protected]>

**st: RE: Interpreting Poisson output***From:*"Kieran McCaul" <[email protected]>

**st: gllamm (poisson) execution time***From:*"Keith Dear (work)" <[email protected]>

**Re: st: AW: gllamm (poisson) execution time***From:*"Keith Dear (home)" <[email protected]>

**Re: st: AW: gllamm (poisson) execution time***From:*Jeph Herrin <[email protected]>

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