The Generalized Weighted Lindley Distribution: Properties, Estimation and Applications

TL;DR

This paper introduces the generalized weighted Lindley distribution, a flexible lifetime model with diverse hazard functions, and compares various estimation methods through simulations and real data applications.

Contribution

It proposes the new GWL distribution, explores its properties, and evaluates multiple estimation techniques, demonstrating its effectiveness over existing models.

Findings

GWL distribution can model various hazard shapes.

Different estimators are compared via simulations.

GWL outperforms several existing lifetime distributions.

Abstract

In this paper, we proposed a new lifetime distribution namely generalized weighted Lindley (GLW) distribution. The GLW distribution is a useful generalization of the weighted Lindley distribution, which accommodates increasing, decreasing, decreasing-increasing-decreasing, bathtub, or unimodal hazard functions, making the GWL distribution a flexible model for reliability data. A significant account of mathematical properties of the new distribution are presented. Different estimation procedures are also given such as, maximum likelihood estimators, method of moments, ordinary and weighted least-squares, percentile, maximum product of spacings and minimum distance estimators. The different estimators are compared by an extensive numerical simulations. Finally, we analyze two data sets for illustrative purposes, proving that the GWL outperform several usual three parameters lifetime distributions.