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On the Construction of Unbiased Estimators for the Group Testing Problem

Abstract

Debiased estimation has long been an area of research in the group testing literature. This has led to the development of several estimators with the goal of bias minimization and, recently, an unbiased estimator based on sequential binomial sampling. Previous research, however, has focused heavily on the simple case where no misclassification is assumed and only one trait is to be tested. In this paper, we consider the problem of unbiased estimation in these broader areas, giving constructions of such estimators for several cases. We show that, outside of the standard case addressed previously in the literature, it is impossible to find any proper unbiased estimator, that is, an estimator giving only values in the parameter space. This is shown to hold generally under any binomial or multinomial sampling plans.

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Acknowledgments

The authors would like to thank the Editor, Associate Editor, and two anonymous referees whose input greatly improved the presentation of this paper.

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Correspondence to Gregory Haber.

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Haber, G., Malinovsky, Y. On the Construction of Unbiased Estimators for the Group Testing Problem. Sankhya A 82, 220–241 (2020). https://doi.org/10.1007/s13171-018-0156-4

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  • DOI: https://doi.org/10.1007/s13171-018-0156-4

Keywords and phrases.

  • Binomial sampling plans
  • Group testing
  • Multinomial sampling plans
  • Sequential estimation
  • Unbiased estimation

AMS (2000) subject classification.

  • Primary 62F10
  • Secondary 62L12