R help - Mar 2005 - cross-validation

I've been looking at the base and Design libraries and it is unclear to me
the best way to approach doing cross-validation. I'm interested in using
temporal (I have five years of data), spatial (I've divided my data set up
into 5 blocks that make sense and have a block variable attached to my data) and
I was also thinking of doing a random cross-validation to look at general model
stability. For the third options I can use cross-validation or bootstrapping.

If someone can type out a code example, that would be very helpful to me. 

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)

On Sun, 13 Mar 2005 15:28:54 -0700
Trevor Wiens <twiens at interbaun.com> wrote:
> I've been looking at the stats and Design libraries and it is unclear
to me the best way to approach doing cross-validation. I'm interested in
using temporal (I have five years of data), spatial (I've divided my data
set up into 5 blocks that make sense and have a block variable attached to my
data) and I was also thinking of doing a random cross-validation to look at
general model stability. For the third option I think either cross-validation or
bootstrapping would be appropriate
> 
> If someone can type out a really simple code example ( or point me to one),
that would be very helpful.
> 
I realized I should have mentioned this is for logistic regression using either
glm or the Design lrm models.

Thanks

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)