@article{Ren2025, 
author = {Haiping Ren and Jiajie Shi},
title = {A generalized Lindley distribution:Properties, estimation and applications under progressively type-Ⅱ censored samples},
year = {2025},
journal = {AIMS Mathematics},
volume = {10},
number = {5},
pages = {10554-10590},
keywords = {progressively type-Ⅱ censored samples, maximum product spacing estimation, Bayesian estimation, Metropolis-Hasting algorithm, asymptotic confidence interval, highest posterior density interval},
url = {https://www.sciopen.com/article/10.3934/math.2025480},
doi = {10.3934/math.2025480},
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.}
}