[R-sig-DCM] number of iterations

Chris Chapman cnchapman at msn.com
Wed Feb 23 17:05:43 CET 2011


Hi Dimitri --

For my part, yes, I think it all depends :-)  The usual recommendation is to 
run it "quite a while" (50k+ iterations) and inspect the convergence of the 
estimates (i.e., plot the draws and see if there are approximately 
horizontal lines after a certain number of iterations, with no "blow ups" of 
individual lines or major crossovers among them).

Personally, I tend to start with 100k iterations (only because I like round 
numbers) and take beta draws every 10 of the final 20k.  If it doesn't 
converge but looks plausible (not all over the place), then I try 200k.  If 
it still doesn't converge, I'll decide what to do based on how bad the 
convergence plots look.  That's assuming something like 6-8 attributes and 
30-40 total levels in a CBC model.

(BTW, for a better answer ... Greg Allenby [one of the authors of bayesm] 
offers tutorials at ART Forum most years that go into the general bayesm 
approach in substantial depth.  I'd bet you've taken that already, though 
:-)

-- Chris

--------------------------------------------------
From: "Dimitri Liakhovitski" <dimitri.dcm at gmail.com>
Sent: Wednesday, February 23, 2011 3:37 PM
To: "R DCM List" <r-sig-dcm at r-project.org>
Subject: [R-sig-DCM] number of iterations

> Question for those who have done HB to assess DCM utilities in bayesm:
>
> I know, this question is too general and it all depends on the nature of 
> the
> DCM at hand, # of attributes, # of levels, etc.
> But in general: when you run HB in bayesm, how many iterations do you run 
> in
> total and how many do you use to grab your beta draws from?
>
> Thank you!
> Dimitri
>
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>
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