Evaluates the first derivative of the link function, given an exponential family distribution, at the expected values. The expected values are estimated with a generalized linear model assuming a Gaussian distribution.
gDerivMu(mu)Fitted values of the model (numeric vector)
Numeric scalar with gives the generalized cross-validation score. The kernel deep stacking network used to calculate the score is available as attribute.
Simon N. Wood, (2006), Generalized Additive Models: An Introduction with R, Taylor \& Francis Group LLC