Does any one know how to do K fold cross validation (with lasso penalty) for quantile regression including the weight of variables ? I found rqPen but it doesn't take account weight of variables.
Linear regression : cv.glmnet(X,Y lambda=..., weigths=colmun_of_weight_data, alpha=1)
rqPen::rq.pen.cv(X,Y,penalty = "LASSO", lambda = lambdas) #but there is no weights here :/
