Optimal precedence tests under single and double-sampling framework

Chakraborty, Niladri and Balakrishnan, Narayanaswamy and Finkelstein, Maxim (2024) Optimal precedence tests under single and double-sampling framework. Journal of Computational and Applied Mathematics, 445. 115805. ISSN 0377-0427 (https://doi.org/10.1016/j.cam.2024.115805)

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Abstract

The precedence test is a nonparametric, two-sample test for stochastic comparison of lifetime data. The power of the precedence test increases with increasing sample size. However, the power curve of the precedence test follows a concave pattern that says the rate of increase in power decreases with increasing sample size. In this article, we intend to find the optimal sample size for the precedence test under the single and double-sampling frameworks. A genetic algorithm is used to find the optimal sample size.

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• Item metadata

  Item type:	Article
  ID code:	89065
  Dates:	Date Event 1 August 2024 Published 19 February 2024 Published Online 8 February 2024 Accepted 15 February 2023 Submitted
  Subjects:	Science > Mathematics
  Department:	Strathclyde Business School > Management Science
  Depositing user:	Pure Administrator
  Date deposited:	01 May 2024 10:20
  Last modified:	11 Nov 2024 14:18
  URI:	https://strathprints.strath.ac.uk/id/eprint/89065