Fisher information matrix for three-parameter exponentiated-Weibull distribution under type II censoring

TL;DR

This paper derives the Fisher information matrix for the three-parameter exponentiated Weibull distribution under type II censoring, providing a computationally feasible approach for inference and illustrating the impact of censoring on estimation.

Contribution

It introduces a new integral representation of the Fisher information matrix and a simple algorithm for maximum likelihood estimation under type II censoring.

Findings

Fisher information matrix expressed as a single integral

Algorithm for maximum likelihood estimation under censoring

Censoring rate affects estimation accuracy

Abstract

This paper considers the three-parameter exponentiated Weibull family under type II censoring. It first graphically illustrates the shape property of the hazard function. Then, it proposes a simple algorithm for computing the maximum likelihood estimator and derives the Fisher information matrix. The latter one is represented through a single integral in terms of hazard function, hence it solves the problem of computation difficulty in constructing inference for the maximum likelihood estimator. Real data analysis is conducted to illustrate the effect of censoring rate on the maximum likelihood estimation.