Moment-type estimators for a weighted exponential family

TL;DR

This paper introduces closed-form moment estimators for weighted exponential families, enhances them with bootstrap bias reduction, and evaluates their performance through Monte Carlo simulations, demonstrating improved accuracy.

Contribution

The paper presents novel closed-form moment estimators for weighted exponential families and introduces a bootstrap bias reduction method, which are evaluated via simulations.

Findings

Bootstrap bias-reduced estimators perform better in simulations

Proposed estimators are computationally efficient

Favorable results shown in Monte Carlo studies

Abstract

In this paper, we propose and study closed-form moment type estimators for a weighted exponential family. We also develop a bias-reduced version of these proposed closed-form estimators using bootstrap techniques. The estimators are evaluated using Monte Carlo simulation. This shows favourable results for the proposed bootstrap bias-reduced estimators.