[R] Logit Model... GLM or GEE or ??

roger koenker rkoenker at uiuc.edu
Fri Aug 7 00:15:57 CEST 2009

You could take a look at:

M West, PJ Harrison, HS Migon - Journal of the American Statistical  
Association, 1985 - jstor.org
Page 1. Dynamic Generalized Linear Models and Bayesian Forecasting

and the subsequent literature it has generated... or along the same  
lines the literature on chess

url:    www.econ.uiuc.edu/~roger            Roger Koenker
email    rkoenker at uiuc.edu            Department of Economics
vox:     217-333-4558                University of Illinois
fax:       217-244-6678                Urbana, IL 61801

On Aug 6, 2009, at 5:00 PM, Noah Silverman wrote:

> Posted about this earlier.  Didn't receive any response
> But, some further research leads me to believe that MAYBE a GLMM or  
> a GEE function will do what I need.
> Hello,
> I have a bit of a tricky puzzle with trying to implement a logit  
> model as described in a paper.
> The particular paper is on horseracing and they explain a model that  
> is a logit trained "per race", yet somehow the coefficients are  
> combined across all the training races to come up with a final set  
> of coefficients.
> My understanding is that they maximize log likelihood across the  
> entire set of training races. Yet this isn't just as standard logit  
> model as they are looking at data "per race".
> This is a bit hard to explain, so I've attached a tiny pdf of the  
> paragraph from the paper explaining this.
> Like everything else in the data/stat/econ world, there is probably  
> a library in R that does this kind of thing, but after 3 days of  
> heavy google research, I've been unable to find it.
> Does anyone have any suggestions??
> Thanks.
> -N
> Attached is a jpg of the book page describing what I'm trying to do...
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