cv.glm {boot}

From: Trevor Wiens

On Tue, 15 Mar 2005 07:05:49 +0000 (GMT)
Prof Brian Ripley <ripley at stats.ox.ac.uk> wrote:

Cross-validation assumes exchangeability of units.  You can 

easily write 

your own code (lots of examples in MASS), but first you 

would need to 

prove the validity of what you are attempting.  For 

example, dropping 

chunks in the middle of a time series is not valid unless 

your prediction 

somehow takes the temporal structure into account (and glm 

does not).

Yes, I'm aware of that and I do have a number of predictors 
which vary with time (from year to year such as precipitation 
or properly timed vegetation indices from each year....) so 
that isn't my problem. Also my spatial blocking is also valid 
(distinct partitions of the study area). I'm also aware of 
the problems of spatial autocorrelation and have taken some 
measures to deal with that. I am however rather new at R and 
not a statistician, so I am heavily reliant on books such as 
Hosmer and Lemeshow or Manley(Resource selection by Animals) 
on procedure. Unforunately, they are not S-plus or R oriented 
so I have some difficulty translating those ideas to R.

You mention lots of examples in MASS regarding 
cross-validation, but I can't find them. Perhaps I'm looking 
in the wrong spot. I've done help.search('validation'), .... 
and found nothing that seemed obviously applicable to my 
problem. I suppose I should pick up a copy of your books 
which would probably be very helpful. However, if it isn't 
too much trouble. I would really appreciate a bit more direct help. 

This is what I assumed I would do somethink like this (in 
this example basp = Baird's Sparrow presence or absence)

train <- birddata[birddata$recordyear != 2000]
test <- birddata[birddata$recordyear == 2000]
train.glm <- glm(basp ~ elev + slope + precip + precip_1 ..., 
data=birddata, family=binomial)
pred <- predict(train.glm, newdata=test, type='response')
actual <- test$basp
what happens next??

Thanks in advance.

T
-- 
Trevor Wiens 
twiens at interbaun.com

The significant problems that we face cannot be solved at the same 
level of thinking we were at when we created them. 
(Albert Einstein)