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Research Article | Open Access

A generalized Lindley distribution:Properties, estimation and applications under progressively type-Ⅱ censored samples

Haiping Ren1( )Jiajie Shi2
Teaching Department of Basic Subjects, Jiangxi University of Science and Technology, Nanchang, 330013, China
College of Science, Jiangxi University of Science and Technology, Ganzhou, 341000, China
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Abstract

A two-parameter generalized Lindley distribution is proposed, whose probability density function contains two models that are particularly well-suited for lifetime studies: the inverted J-type and the unimodal left-leaning type. Some of the main numerical characteristics of the proposed distribution were investigated. Additionally, based on progressively type-Ⅱ censored samples, three estimation methods were used to estimate the parameters, reliability function, and hazard function of the distribution: maximum product spacing estimation, maximum likelihood estimation, and Bayesian estimation. Bayesian estimators were obtained under squared error and general entropy loss functions, and the Metropolis-Hastings algorithm was used to obtain Bayesian estimates. In addition to point estimation, corresponding asymptotic confidence intervals and the highest posterior density intervals were also studied. Through Monte Carlo simulation, we measured the performance of the three estimators using four criteria. Finally, the ability of the proposed distribution to accurately fit the data was demonstrated using a real dataset.

CLC number: 62E10; 62F10

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AIMS Mathematics
Pages 10554-10590

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Cite this article:
Ren H, Shi J. A generalized Lindley distribution:Properties, estimation and applications under progressively type-Ⅱ censored samples. AIMS Mathematics, 2025, 10(5): 10554-10590. https://doi.org/10.3934/math.2025480

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Received: 27 February 2025
Revised: 10 April 2025
Accepted: 15 April 2025
Published: 15 May 2025
©2025 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)