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 
[EMAIL PROTECTED]

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

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