Hi!
When I use the glm.cv function I get a value called "delta" which is explained
as the "raw cross-validation estimate of prediction error". I recently found a
formula for that term in literature where it is defined as:
alpha = 1 / N * sum over( yi - yi,pred,CV)
Well it is somehow similar to the RSS for R2 and the PRESS for Q2.
But this delta value increases with increasing R2 for the same fitted model
I assumend that an error-value would sink with a better fit.
So what is the mathmetical equation that lies behind this delta value?
Best regards for your help,
Markus
---------------------------------
[[alternative HTML version deleted]]
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
