Advertisement

Minimax Regret Sampling Plans Based on Generalized Moments of the Prior Distribution

  • W. Seidel
Part of the Frontiers in Statistical Quality Control 4 book series (FSQC, volume 4)

Abstract

In acceptance sampling, one is often interested in finding sampling plans that incorporate prior information about the fraction of defective items in incoming lots in order to minimize costs. If a prior distribution of the fraction defective is known, a Bayesian sampling plan may be used. Some authors, however, consider this situation to be unlikely and therefore have developed sampling plans based only on incomplete prior information.

Keywords

Prior Distribution Prior Information Sampling Plan Defective Item Acceptance Sampling 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [l]
    Bruhn—Suhr, M. (1988): Kostenoptimale Variablenprüfpläne für den Fall der Normalverteilung mit unbekannter Varianz. Dissertation, Universität der Bundeswehr Hamburg.Google Scholar
  2. [2]
    BruhnSuhr, M. and KRUMBHOLZ, W. (1990): A new variables sampling plan for normally distributed lots with unknown standard deviation and double specification limits, Statistical Papers Vol. 31, 195–207.Google Scholar
  3. [3]
    Collani, E. v. (1986): The a—optimal sampling scheme, Journal of Quality Technology Vol. 18, 63–66.Google Scholar
  4. [4]
    Collani, E. v. and Unterschemmann, H. (1989): Alpha—optimal sampling plans for variables in the one—sided case. Institut für Angewandte Mathematik und Statistik, Würzburg.Google Scholar
  5. [5]
    Collani, E. v. and Unterschemmann, H. (1989): Alpha-optimal sampling plans for variables in the two—sided case. Institut für Angewandte Mathematik und Statistik, Würzburg.Google Scholar
  6. [6]
    Krumbholz, W. (1982): Die Bestimmung einfacher Attributprüfpläne unter Berücksichtigung von unvollständiger Vorinformation, Allgemeines Stat. Archiv Vol. 66, 240–253.Google Scholar
  7. [7]
    Krumbholz, W. and Schröder, J. (1987): Zur Ausnutzung unvollständiger Vorinformation bei der Minimax—Regret—Methode, Allgemeines Stat. Archiv Vol. 71, 117–125.Google Scholar
  8. [8]
    Schröder, J. (1987): Möglichkeiten der Minimax—Regret—Methode bei der messenden Prüfung. Dissertation, Universität der Bundeswehr Hamburg.Google Scholar
  9. [9]
    Stange, K. (1964): Die Berechnung wirtschaftlicher Pläne für die messende Prüfung, Metrika Vol. 8, 48–82.MathSciNetGoogle Scholar
  10. Winkler, G. (1982): Integral representation and upper bounds for stop—loss premiums under constraints given by inequalities, Scand. Actuarial J. 15–21.Google Scholar
  11. [11]
    Winkler, G. (1988): Extreme points of moment sets, Mathematics of Operations Research Vol. 13, 581–587.zbMATHCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1992

Authors and Affiliations

  • W. Seidel
    • 1
  1. 1.HamburgGermany

Personalised recommendations