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Sampling inspection by variables: nonparametric setting

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  • Ansgar Steland
  • Henryk Zähle

Abstract

A classic statistical problem is the optimal construction of sampling plans to accept or reject a lot based on a small sample. We propose a new asymptotically optimal solution for acceptance sampling by variables setting where we allow for an arbitrary unknown underlying distribution. In the course of this, we assume that additional sampling information is available, which is often the case in real applications. That information is given by additional measurements which may be affected by a calibration error. Our results show that, first, the proposed decision rule is asymptotically valid under fairly general assumptions. Secondly, the estimated optimal sample size is asymptotically normal. Furthermore, we illustrate our method by a real data analysis and investigate to some extent its finite‐sample properties and the sharpness of our assumptions by simulations.

Suggested Citation

  • Ansgar Steland & Henryk Zähle, 2009. "Sampling inspection by variables: nonparametric setting," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 63(1), pages 101-123, February.
    • Handle: RePEc:bla:stanee:v:63:y:2009:i:1:p:101-123
    DOI: 10.1111/j.1467-9574.2008.00413.x
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    References listed on IDEAS

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    1. David H. Baillie & Chris A. J. Klaassen, 2006. "Credit to and in acceptance sampling," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 60(3), pages 283-291, August.
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    Cited by:

    1. Wolfgang Kössler & Janine Ott, 2019. "Two-sided variable inspection plans for arbitrary continuous populations with unknown distribution," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 103(3), pages 437-452, September.
    2. Golyandina, Nina & Pepelyshev, Andrey & Steland, Ansgar, 2012. "New approaches to nonparametric density estimation and selection of smoothing parameters," Computational Statistics & Data Analysis, Elsevier, vol. 56(7), pages 2206-2218.

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