Haber, GregoryMalinovsky, Yaakov2018-02-152018-02-152018http://hdl.handle.net/11603/7794Debiased 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.16 pagesen-USThis 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.Binomial sampling plansGroup testingMultinomial sampling plansSequential estimationUnbiased estimationText