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Robust inference and model selection for data from one-shot devices under cyclic accelerated life-tests with an application to a test of CSP solder joints

Author

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  • Narayanaswamy Balakrishnan
  • Elena Castilla

Abstract

We introduce here a new family of divergence-based estimators in this work for predicting the lifetimes of one-shot devices subjected to cyclic Accelerated Life-Tests (ALTs). This family, which includes the maximum likelihood estimator (MLE) as a special case, offers a robust alternative to traditional inferential procedures. We also present a family of divergence-based model selection criteria. A simulation study and a numerical example illustrate the advantages of these estimators and the robust inferential methods based on them.

Suggested Citation

  • Narayanaswamy Balakrishnan & Elena Castilla, 2025. "Robust inference and model selection for data from one-shot devices under cyclic accelerated life-tests with an application to a test of CSP solder joints," Journal of Risk and Reliability, , vol. 239(5), pages 900-914, October.
    • Handle: RePEc:sae:risrel:v:239:y:2025:i:5:p:900-914
    DOI: 10.1177/1748006X251314506
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    References listed on IDEAS

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    1. Ling, M.H. & Hu, X.W., 2020. "Optimal design of simple step-stress accelerated life tests for one-shot devices under Weibull distributions," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    2. Cheng, Yao & Elsayed, Elsayed A., 2017. "Reliability modeling of mixtures of one-shot units under thermal cyclic stresses," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 58-66.
    3. Xiaojun Zhu & Kai Liu, 2022. "Reliability of one-shot device with generalized gamma lifetime under cyclic accelerated life-test," Journal of Risk and Reliability, , vol. 236(6), pages 1007-1023, December.
    4. G. Avlogiaris & A. C. Micheas & K. Zografos, 2019. "A Criterion for Local Model Selection," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 81(2), pages 406-444, December.
    5. N. Balakrishnan & Debasis Kundu, 2019. "Birnbaum‐Saunders distribution: A review of models, analysis, and applications," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 35(1), pages 4-49, January.
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