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Pairwise model discrimination with applications in lifetime distributions and degradation processes

Author

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  • Piao Chen
  • Zhi‐Sheng Ye
  • Xun Xiao
Abstract
Reliability data obtained from life tests and degradation tests have been extensively used for purposes such as estimating product reliability and predicting warranty costs. When there is more than one candidate model, an important task is to discriminate between the models. In the literature, the model discrimination was often treated as a hypothesis test and a pairwise model discrimination procedure was carried out. Because the null distribution of the test statistic is unavailable in most cases, the large sample approximation and the bootstrap were frequently used to find the acceptance region of the test. Although these two methods are asymptotically accurate, their performance in terms of size and power is not satisfactory in small sample size. To enhance the small‐sample performance, we propose a new method to approximate the null distribution, which builds on the idea of generalized pivots. Conventionally, the generalized pivots were often used for interval estimation of a certain parameter or function of parameters in presence of nuisance parameters. In this study, we further extend the idea of generalized pivots to find the acceptance region of the model discrimination test. Through extensive simulations, we show that the proposed method performs better than the existing methods in discriminating between two lifetime distributions or two degradation models over a wide range of sample sizes. Two real examples are used to illustrate the proposed methods.

Suggested Citation

  • Piao Chen & Zhi‐Sheng Ye & Xun Xiao, 2019. "Pairwise model discrimination with applications in lifetime distributions and degradation processes," Naval Research Logistics (NRL), John Wiley & Sons, vol. 66(8), pages 675-686, December.
    • Handle: RePEc:wly:navres:v:66:y:2019:i:8:p:675-686
    DOI: 10.1002/nav.21875
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    References listed on IDEAS

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    5. Philip L.H. Yu & Thomas Mathew & Yuanyuan Zhu, 2017. "A generalized pivotal quantity approach to portfolio selection," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(8), pages 1402-1420, June.
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    Cited by:

    1. Hui Xiao & Kunxiang Yi & Gang Kou & Liudong Xing, 2020. "Reliability of a two‐dimensional demand‐based networked system with multistate components," Naval Research Logistics (NRL), John Wiley & Sons, vol. 67(6), pages 453-468, September.

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