Dear all:
I have a question about how to get the optimal estimate of coefficients
using the penalized quantile regression (LASSO penalty in quantile
regression defined in Koenker 2005).
In R, I found both
rq(y ~ x, method="lasso",lambda = 30) and
rq.fit.lasso(x, y, tau = 0.5, lambda = 1, beta = .9995, eps = 1e-06)
can give the estimates. But, I didn't find a way using either of these
command to get the optimal estimates. Is there any way to specify the
optimal lambda (the value of penalty parameter) and then get the optimal
estimates? Thanks a lot. Any comment will be appreciated.
sophie
[[alternative HTML version deleted]]
