simple.ridge: Simple Ridge Regression

In ElemStatLearn: Data Sets, Functions and Examples from the Book: "The Elements of Statistical Learning, Data Mining, Inference, and Prediction" by Trevor Hastie, Robert Tibshirani and Jerome Friedman

Description

Function to do simple ridge regression.

Usage

   simple.ridge(x, y, lambda = 1, df, ...)

Arguments

x	predictor matrix, NA's not allowed. Should not include a column of 1's.
y	response matrix, NA's not allowed
lambda	vector of ridge coefficients
df	vector of target degrees of freedom. lambda is calculated from these.
...	Presently not used

Details

Principal advantage with this compared to other implementations of ridge regression in R is that we can do the calculations for multiple degrees of freedom at once. Ridging is not applied to the intercept.

Value

List with components:

beta0	intercept
beta	matrix of coefficients. One column for each lambda
lambda	lambda used
df	df used

Author(s)

Kjetil B. Halvorsen

Examples

# See examples for \link{prostate}.

Example output

ElemStatLearn documentation built on Aug. 12, 2019, 9:04 a.m.