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Testing for the validity of the assumptions in the exponential step-stress accelerated life-testing model

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  • Wang, Bing Xing

Abstract

In the application of the exponential step-stress accelerated life-testing model, there are usually three assumptions required: (1) for any stress level, the lifetime distribution of a test unit is exponential; (2) for any stress level, the mean life of a test unit is a log-linear function of stress; (3) a cumulative exposure model holds. This paper explores the validity of assumptions 1 and 3. It is proved that assumption 3 is unnecessary to the exponential step-stress accelerated life-testing model. A test statistic is proposed to test the validity of the assumptions 1. The null distribution of the test statistic is derived. A Monte Carlo simulation is given to study the power of the proposed test procedure. Finally, an example is given to illustrate the proposed test procedure.

Suggested Citation

  • Wang, Bing Xing, 2009. "Testing for the validity of the assumptions in the exponential step-stress accelerated life-testing model," Computational Statistics & Data Analysis, Elsevier, vol. 53(7), pages 2702-2709, May.
  • Handle: RePEc:eee:csdana:v:53:y:2009:i:7:p:2702-2709
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    References listed on IDEAS

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    1. Ronghua Wang & Heliang Fei, 2004. "Conditions for the coincidence of the TFR, TRV and CE models," Statistical Papers, Springer, vol. 45(3), pages 393-412, July.
    2. Norbert Henze & Simos G. Meintanis, 2005. "Recent and classical tests for exponentiality: a partial review with comparisons," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 61(1), pages 29-45, February.
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    Cited by:

    1. Kateri, Maria & Kamps, Udo & Balakrishnan, Narayanaswamy, 2011. "Optimal allocation of change points in simple step-stress experiments under Type-II censoring," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 236-247, January.
    2. Qin, Shuidan & Wang, Bing Xing & Wu, Wenhui & Ma, Chao, 2022. "The prediction intervals of remaining useful life based on constant stress accelerated life test data," European Journal of Operational Research, Elsevier, vol. 301(2), pages 747-755.
    3. Kong, Yaonan & Ye, Zhisheng, 2017. "Goodness-of-fit tests in the multi-state Markov model," Reliability Engineering and System Safety, Elsevier, vol. 166(C), pages 16-24.

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