gDerivMu: Derivative of the link function evaluated at the expected...
In kernDeepStackNet: Kernel Deep Stacking Networks

Description Usage Arguments Value Note Author(s) References See Also

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.

1	gDerivMu(mu)

`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.

This function is not intended to be called directly by the user. Should only be used by experienced users, who want to customize the model.

Thomas Welchowski welchow@imbie.meb.uni-bonn.de

Simon N. Wood, (2006), Generalized Additive Models: An Introduction with R, Taylor \& Francis Group LLC

calcTrA, calcWdiag, varMu

kernDeepStackNet documentation built on May 2, 2019, 8:16 a.m.