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Applications of the Fractional-Random-Weight Bootstrap

Author

Listed:
  • Li Xu
  • Chris Gotwalt
  • Yili Hong
  • Caleb B. King
  • William Q. Meeker

Abstract

For several decades, the resampling based bootstrap has been widely used for computing confidence intervals (CIs) for applications where no exact method is available. However, there are many applications where the resampling bootstrap method cannot be used. These include situations where the data are heavily censored due to the success response being a rare event, situations where there is insufficient mixing of successes and failures across the explanatory variable(s), and designed experiments where the number of parameters is close to the number of observations. These three situations all have in common that there may be a substantial proportion of the resamples where it is not possible to estimate all of the parameters in the model. This article reviews the fractional-random-weight bootstrap method and demonstrates how it can be used to avoid these problems and construct CIs in a way that is accessible to statistical practitioners. The fractional-random-weight bootstrap method is easy to use and has advantages over the resampling method in many challenging applications.

Suggested Citation

  • Li Xu & Chris Gotwalt & Yili Hong & Caleb B. King & William Q. Meeker, 2020. "Applications of the Fractional-Random-Weight Bootstrap," The American Statistician, Taylor & Francis Journals, vol. 74(4), pages 345-358, October.
    • Handle: RePEc:taf:amstat:v:74:y:2020:i:4:p:345-358
    DOI: 10.1080/00031305.2020.1731599
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    Cited by:

    1. Jie Min & Yili Hong & Caleb B. King & William Q. Meeker, 2022. "Reliability analysis of artificial intelligence systems using recurrent events data from autonomous vehicles," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(4), pages 987-1013, August.
    2. Zhuang, Liangliang & Xu, Ancha & Pang, Jihong, 2021. "Product reliability analysis based on heavily censored interval data with batch effects," Reliability Engineering and System Safety, Elsevier, vol. 212(C).

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