Comparison Between Some of Penalized Estimators for High Dimensional Quantile Regression

Abstract

In this research, many of penalized estimator have been compared in the quantile regression model with high dimensions, and these estimator are (ridge - lasso - elastic net). The process of comparison among of those estimators were done by simulation and based on statistical measures, root mean predictive error, false positive rate ( FPR) and false negative rate (FNR).Simulation results show that an elastic net estimator is the best of other estimators.