Exact Likelihood-Ratio Tests for a Simple Step-Stress Cumulative Exposure Model with Censored Exponential Data

Xiaojun Zhu (), N. Balakrishnan and Yiliang Zhou
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Xiaojun Zhu: Xi’an Jiaotong-Liverpool University
N. Balakrishnan: McMaster University
Yiliang Zhou: WuXi AppTec (Suzhou) Co., Ltd.

Methodology and Computing in Applied Probability, 2020, vol. 22, issue 2, 497-509

Abstract: Abstract An accelerated life test (ALT) is commonly used in reliability studies of high quality products. A step-stress experiment is one such ALT that is often used in practice. In this paper, we develop exact inference based on likelihood-ratio test for a simple step-stress model with exponential lifetimes under Type-II censoring. We consider both unrestricted and order-restricted maximum likelihood estimators (MLEs) for this purpose. We also derive the exact power function of this test, which we then use for designing an optimal step-stress testing experiment. By using a similar approach, we extend these results to other forms of censoring. Monte Carlo simulations are then carried out to evaluate the performance of the inferential methods developed here. Finally, an illustrative example is presented for demonstrating all the inferential results.

Keywords: Accelerated life-test; Exact distribution; Likelihood-ratio test; Order-restricted MLEs; Optimal design; Unrestricted MLEs; 62E15; 62F03; 62F30; 62N01; 62N05 (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s11009-019-09719-3

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