On Admissibility in Bipartite Incidence Graph Sampling

Abstract

In bipartite incidence graph sampling, the target study units may be formed as connected population elements, which are distinct to the units of sampling and there may exist generally more than one way by which a given study unit can be observed via sampling units. This generalizes finite-population element or multistage sampling, where each element can only be sampled directly or via a single primary sampling unit. We study the admissibility of estimators in bipartite incidence graph sampling and identify other admissible estimators than the classic Horvitz-Thompson estimator. Our admissibility results encompass those for finite-population sampling.