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Rao-Blackwellization is used to improve the unbiased Hansen–Hurwitz and Horvitz–Thompson unbiased estimators in Adaptive Cluster
Sampling by finding the conditional expected value of the original unbiased estimators given the sufficient or minimal sufficient
statistic. In principle, the same idea can be used to find better ratio estimators, however, the calculation of taking all
the possible combinations into account can be extremely tedious in practice. The simplified analytical forms of such ratio
estimators are not currently available. For practical interest, several improved ratio estimators in Adaptive Cluster Sampling
are proposed in this article. The proposed ratio estimators are not the real Rao-Blackwellized versions of the original ones
but make use of the Rao-Blackwellized univariate estimators. How to calculate the proposed estimators is illustrated, and
their performance are evaluated by both of the Bivariate Poisson clustered process and a real data. The simulation result
indicates that the proposed improved ratio estimators are able to provide considerably advantageous estimation results over
the original ones. 相似文献