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,
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