On the construction of unbiased estimators for the group testing problem

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dc.contributor.authorHaber, Gregory
dc.contributor.authorMalinovsky, Yaakov
dc.date.accessioned2018-02-15T13:53:17Z
dc.date.available2018-02-15T13:53:17Z
dc.date.issued2018
dc.description.abstractDebiased estimation has long been an area of research in the group testing litera-ture. This has led to the development of many estimators minimizing bias and, most 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, out-side 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.en_US
dc.description.urihttps://arxiv.org/abs/1801.10547en_US
dc.format.extent16 pagesen_US
dc.identifierdoi:10.13016/M2319S452
dc.identifier.urihttp://hdl.handle.net/11603/7794
dc.language.isoen_USen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Mathematics Department Collection
dc.relation.ispartofUMBC Faculty Collection
dc.relation.ispartofUMBC Student Collection
dc.rightsThis item may be protected under Title 17 of the U.S. Copyright Law. It is made available by UMBC for non-commercial research and education. For permission to publish or reproduce, please contact the author.
dc.subjectBinomial sampling plansen_US
dc.subjectGroup testingen_US
dc.subjectMultinomial sampling plansen_US
dc.subjectSequential estimationen_US
dc.subjectUnbiased estimationen_US
dc.titleOn the construction of unbiased estimators for the group testing problemen_US
dc.typeTexten_US

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