QR.ip {cqrReg} | R Documentation |
Quantile Regression (QR) use Interior Point (ip) Method
Description
The function use the interior point method from quantreg to solve the quantile regression problem.
Usage
QR.ip(X,y,tau)
Arguments
X |
the design matrix |
y |
response variable |
tau |
quantile level |
Value
a list
structure is with components
beta |
the vector of estimated coefficient |
b |
intercept |
Note
Need to install quantreg package from CRAN.
References
Koenker, Roger. Quantile Regression, New York, 2005. Print.
Koenker, R. and S. Portnoy (1997). The Gaussian Hare and the Laplacian Tortoise: Computability of squared-error vs. absolute-error estimators, with discussion, Statistical Science, 12, 279-300.
Examples
set.seed(1)
n=100
p=2
a=rnorm(n*p, mean = 1, sd =1)
x=matrix(a,n,p)
beta=rnorm(p,1,1)
beta=matrix(beta,p,1)
y=x%*%beta-matrix(rnorm(n,0.1,1),n,1)
# x is 1000*10 matrix, y is 1000*1 vector, beta is 10*1 vector
#you should install Rmosek first to run following command
#QR.ip(x,y,0.1)
[Package cqrReg version 1.2.1 Index]