regpro (version 0.1.1)

linear.quan: Multivariate linear quantile regression estimator

Description

Computes the estimates of parameters for a linear quantile regression estimator.

Usage

linear.quan(x, y, p=0.5)

Arguments

x

n*d data matrix; the matrix of the values of the explanatory variables

y

n vector; the values of the response variable

p

0

Value

beta0 is the estimate of the intercept and beta1 is the vector containing the estimates of the coefficients

Details

numerical optimization is used in the calculation

See Also

linear,

Examples

set.seed(1)
n<-100
d<-2 
x<-8*matrix(runif(n*d),n,d)-3
C<-(2*pi)^(-d/2)
phi<-function(x){ return( C*exp(-sum(x^2)/2) ) }
D<-3; c1<-c(0,0); c2<-D*c(1,0); c3<-D*c(1/2,sqrt(3)/2)
func<-function(x){phi(x-c1)+phi(x-c2)+phi(x-c3)}
y<-matrix(0,n,1)
for (i in 1:n) y[i]<-func(x[i,])+0.01*rnorm(1)

linear.quan(x,y)