ridge_regression: Ridge Regression

In lyran92/bis557: What the Package Does (One Line, Title Case)

Description

This is a function to implement a ridge regression function taking into account colinear (or nearly colinear) regression variables.

Usage

ridge_regression(X, Y, lambda)

Arguments

X	The input design matrix.
Y	The input response vector.
lambda	The input penalty parameter.

Value

A list of estimated coefficients.

Examples

n <- 1000
p <- 5
beta <- c(1,-1,0,0,2)
set.seed(2)
X <- matrix(rnorm(n*p), nrow=n, ncol = p)
alpha <- 0.05
X[,1] <- X[,1]*alpha+X[,2]*(1 - alpha)
set.seed(1)
Y <- X %*% beta + rnorm(n)
model <- ridge_regression(X, Y, lambda=0.5)
model$coefficients

lyran92/bis557 documentation built on Dec. 21, 2020, 10:03 p.m.