Re:

["Donald Catanzaro, PhD" <dgcatanzaro@gmail.com>]

Hi All,

My apologies to the list as I lurch forward in my humble quest to 
cross-validate my dataset.  As folks have seen it is going rather slower 
than I had hoped which is mainly due to my own lacking than anything else.
I've been working on subsetting my dataset into an 80/20 split and 
creating a model with the 80% data and then using the remaining 20% for 
model validation.  For performance measures of the 80% model I'd like to 
use the AIC and BIC coming from the 20% validation dataset.
It is rather nice that glm includes a subset option so I can create my 
model using 80% of the data when supplied with the correct vector. 

Is there a similar option where I can run the 20% data through the 80% 
derived GLM and thus pull out the deviance & log-likelihoods without 
additional calculations ?
If not, if I understand correctly, my other option would be to:
A)  predict the 80% data points from the 80% model
B)  find mu and size of the 80% predicted data points using fitdistr
C) calculate the log likelihood of the 20% validation dataset using mu 
and size from the 80% predicted data points
D)  calculate AIC and BIC from that log-likelihood

If I can't run the 20% data through my 80% model, would A-D get me where 
I'd like to be ?
--

-Don 

Don Catanzaro, PhD                  Landscape Ecologist
dgcatanzaro@gmail.com               16144 Sigmond Lane
479-751-3616                        Lowell, AR 72745