gettingtothebottom (version 3.0)

quantreglp: Linear Programming - Linear programming solver for quantile regression

Description

quantreglp Function for performing quantile regression using linear programming

Usage

quantreglp(y, X, tau = 0.5, lambda = 0)

Arguments

y

An mx1 vector containing the response variables in the model

X

An nxp matrix containing the predicting variables in the model

tau

(optional) quantile

lambda

(optional) regularization parameter

Examples

set.seed(12345)
n <- 20
p <- 20
X <- matrix(rnorm(n*p),n,p)
b0 <- double(p)
k <- 4
b0[sample(1:p,k,replace=FALSE)] <- 10*rnorm(k)
y <- X%*%b0 + 0.1*rnorm(n)

lambda <- 2
tau <- 0.5
sol <- quantreglp(y,X,tau,lambda)