Bias-reduced estimators of the Weibull tail-coefficient

TL;DR

This paper introduces a bias-reduced estimator for the Weibull tail-coefficient using a regression model and least-squares approach, demonstrating its asymptotic normality and efficiency through simulations.

Contribution

It presents a novel bias-reduction method for estimating the Weibull tail-coefficient based on a regression model and least-squares, with proven asymptotic properties.

Findings

Estimator is asymptotically normal

Simulation confirms estimator's efficiency

Bias reduction improves estimation accuracy

Abstract

In this paper, we consider the problem of the estimation of a Weibull tail-coefficient. In particular, we propose a regression model, from which we derive a bias-reduced estimator. This estimator is based on a least-squares approach. The asymptotic normality of this estimator is also established. A small simulation study is provided in order to prove its efficiency.