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Inference and expected total test time for step-stress life test in the presence of complementary risks and incomplete data

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  • Yajie Tian

    (Beijing Jiaotong University)

  • Wenhao Gui

    (Beijing Jiaotong University)

Abstract

The complementary risk is common and important in the engineering field. However, there is not much research about it because of its complex derivation compared with the competing risk model. In this paper, we concentrate on inference of step-stress partially accelerated life test in the presence of complementary risks under progressive type-II censoring scheme. The Weibull distribution is chosen as the baseline lifetime of the model. The tampered random variable model is adopted as the statistical acceleration model in the accelerated test. We apply both the classical and Bayesian methods to obtain the estimation of lifetime parameters and acceleration factors. The reliability and reversed hazard rate are estimated based on the parametric estimates. The computational formulae of expected total test time are creatively derived under the step-stress and censored setting. The theoretical calculations are compared with simulated values to verify the derivation. Also, numerical studies including the simulation study and real-data analysis in engineering background are conducted to compare and illustrate the performance of the approaches proposed in the paper. Some conclusions and suggestions for actual production are given at the end of the paper.

Suggested Citation

  • Yajie Tian & Wenhao Gui, 2024. "Inference and expected total test time for step-stress life test in the presence of complementary risks and incomplete data," Computational Statistics, Springer, vol. 39(2), pages 1023-1060, April.
    • Handle: RePEc:spr:compst:v:39:y:2024:i:2:d:10.1007_s00180-023-01343-7
    DOI: 10.1007/s00180-023-01343-7
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    References listed on IDEAS

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    1. Manoj Chacko & Rakhi Mohan, 2019. "Bayesian analysis of Weibull distribution based on progressive type-II censored competing risks data with binomial removals," Computational Statistics, Springer, vol. 34(1), pages 233-252, March.
    2. Hon Keung Tony Ng & Debasis Kundu & Ping Shing Chan, 2009. "Statistical analysis of exponential lifetimes under an adaptive Type‐II progressive censoring scheme," Naval Research Logistics (NRL), John Wiley & Sons, vol. 56(8), pages 687-698, December.
    3. Arnab Koley & Debasis Kundu, 2021. "Analysis of progressive Type‐II censoring in presence of competing risk data under step stress modeling," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 75(2), pages 115-136, May.
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