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

       
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