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AIMS Mathematics

2024, Volume 9, Issue 2: 4649-4664. doi: 10.3934/math.2024224
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Nonparametric bootstrap methods for hypothesis testing in the event of double-censored data

  • Department of Mathematics, College of Science, Qassim University, P.O. Box 6644, Buraydah 51452, Saudi Arabia
  • Received: 30 November 2023 Revised: 05 January 2024 Accepted: 12 January 2024 Published: 19 January 2024

  • MSC : 62G09

  • This paper illustrated how nonparametric bootstrap methods for double-censored data can be used to conduct some hypothesis tests, such as quartiles' hypothesis tests. Through simulation studies, the smoothed bootstrap (SB) method performed better results than Efron's method in most scenarios, particularly for small datasets. The SB method provided smaller discrepancies between the actual and nominal error rates.

    Citation: Asamh Saleh M. Al Luhayb. Nonparametric bootstrap methods for hypothesis testing in the event of double-censored data[J]. AIMS Mathematics, 2024, 9(2): 4649-4664. doi: 10.3934/math.2024224

    Related Papers:

  • This paper illustrated how nonparametric bootstrap methods for double-censored data can be used to conduct some hypothesis tests, such as quartiles' hypothesis tests. Through simulation studies, the smoothed bootstrap (SB) method performed better results than Efron's method in most scenarios, particularly for small datasets. The SB method provided smaller discrepancies between the actual and nominal error rates.


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