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
ratings.
url: www.econ.uiuc.edu/~roger Roger Koenker
email rkoen...@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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