Novel closed-form point estimators for a weighted exponential family derived from likelihood equations

Abstract

In this paper, we propose and investigate closed-form point estimators for a weighted exponential family. We also develop a bias-reduced version of these proposed closed-form estimators through bootstrap methods. Estimators are assessed using a Monte Carlo simulation, revealing favorable results for the proposed bootstrap bias-reduced estimators.