Document Type

Article

Publication Date

12-2022

Keywords

the alpha power inverse Weibull distribution, step stress partially accelerated life testing, adaptive progressive hybrid censored data, loss functions

Abstract

Accelerated life tests are used to explore the lifetime of extremely reliable items by subjecting them to elevated stress levels from stressors to cause early failures, such as temperature, voltage, pressure, and so on. The alpha power inverse Weibull (APIW) distribution is of great significance and practical applications due to its appealing characteristics, such as its flexibilities in the probability density function and the hazard rate function. We analyze the step stress partially accelerated life testing model with samples from the APIW distribution under adaptive type II progressively hybrid censoring. We first obtain the maximum likelihood estimates and two types of approximate confidence intervals of the distributional parameters and then derive Bayes estimates of the unknown
parameters under different loss functions. Furthermore, we analyze three probable optimum test techniques for identifying the best censoring under different optimality criteria methods. We conduct simulation studies to assess the finite sample performance of the proposed methodology. Finally, we provide a real data example to further demonstrate the proposed technique.

Comments

Originally published as:

Alotaibi, R.; Almetwally, E.M.; Hai, Q.; Rezk, H. Optimal Test Plan of Step Stress Partially Accelerated Life Testing for Alpha Power Inverse Weibull Distribution under Adaptive Progressive Hybrid Censored Data and Different Loss Functions. Mathematics 2022, 10, 4652. https://doi.org/10.3390/math10244652

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Download

Included in

Mathematics Commons

COinS