Statistical inference for the generalized inverse exponential distribution under progressive first failure censoring scheme

Zhaohui Li

doi:10.1117/12.3051594

18 November 2024 Statistical inference for the generalized inverse exponential distribution under progressive first failure censoring scheme

Zhaohui Li

Author Affiliations +

Proceedings Volume 13403, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2024) ; 134030D (2024) https://doi.org/10.1117/12.3051594
Event: International Conference on Algorithms, High Performance Computing, and Artificial Intelligence, 2024, Zhengzhou, China

Abstract

This article considers the point estimations and interval estimations for a generally inverse exponential distribution on the basis of the progressive first failure censoring. We derive the maximum likelihood estimators along with corresponding asymptotic confidence interval at first. Next, we compute the maximum likelihood through the utilization of the Expectation Maximization (EM) algorithm. Afterwards, Bayesian inference is applied using both symmetric and asymmetric loss functions in scenarios involving either informative or non-informative priors. The M-H algorithm is utilized to compute point estimation, which leads to the highest posterior density credible intervals simultaneously. Eventually, a numerical simulation test is executed for the sake of evaluating the qualities of estimations mentioned and authentic dataset is investigated.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Zhaohui Li "Statistical inference for the generalized inverse exponential distribution under progressive first failure censoring scheme", Proc. SPIE 13403, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2024) , 134030D (18 November 2024); https://doi.org/10.1117/12.3051594

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