Linear programming methods for estimating quantile regression with the application

Abstract

This paper deals with a quantile regression for estimating conditional quantiles, also it deals with two methods for detecting leverage and outlier observations. To determine the best algorithm for estimating the parameters of the quantile regression for the thalassemia data in Mosul city. Three algorithms compared for regression estimation, which are simplex algorithm, smoothing algorithm, and interior point algorithm. Markov chain marginal bootstrap used to compute the confidence intervals.