Regression estimators for the tail index

We propose a class of weighted least squares estimators for the tail index distribution function with regularly varying tail. Our approach is based on method developed by Holan and McElroy (2010) Parzen index. prove asymptotic normality consistency under suitable assumptions. These earlier are compared in various models through simulation study using mean squared error as criterion. The results show that estimator has good performance.