Re: [R] Help with a specific quantile regression problem

What ensures that the tau-th quantile of the residuals is (nearly) zero, is that there IS an intercept in the model, this is one of the conditions required for the subgradient to contain 0 provided there is an intercept, when there is no intercept there is constraint to enforce this any more. u

[R] Help with a specific quantile regression problem

Dear R community, I am a beginner in quantile regression and I have a question about a specific problem. I have used the quantreg package to fit a QR with inequality constrains: n <- 100 p <- 5 X <- matrix(rnorm(n*p),n,p) y <- 0.95*apply(X,1,sum)+rnorm(n) R <- cbind(0,rbind(diag(p),-diag(p))) r <