ridge: Ridge Penalty

In lqa: Penalized Likelihood Inference for GLMs

Description

Object of the penalty class to handle the ridge penalty (Hoerl \& Kennard, 1970).

Usage

ridge(lambda = NULL, ...)

Arguments

lambda	regularization parameter. This must be a nonnegative real number.
...	further arguments.

Details

The ‘classic’ penalty as introduced in Hoerl \& Kennard (1970). The ridge penalty is defined as

P_λ^r (\boldsymbol{β}) = λ ∑_{i=1}^p β_j^2.

Value

An object of the class penalty. This is a list with elements

penalty	character: the penalty name.
lambda	double: the (nonnegative) regularization parameter.
getpenmat	function: computes the diagonal penalty matrix.

Author(s)

Jan Ulbricht

References

Hoerl, A. E. \& R. W. Kennard (1970) Ridge Regression: Bias estimation for nonorthogonal problems. Technometrics 12, 55–67.

See Also

penalty, lasso, penalreg, ForwardBoost

lqa documentation built on May 30, 2017, 3:41 a.m.