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Optimal and Robust Strategies for Cluster Sampling

 

作者: S.M. Tam,  

 

期刊: Journal of the American Statistical Association  （Taylor Available online 1995）
卷期: Volume 90, issue 429  

页码: 379-382

 

ISSN:0162-1459

 

年代: 1995

 

DOI:10.1080/01621459.1995.10476523

 

出版商: Taylor & Francis Group

 

关键词: Best linear unbiased predictor;Finite population sampling;Lower bound;Superpopulation model

 

数据来源: Taylor

 

摘要:

This article extends Royall's (1992) results on optimal and robust sampling strategies to cluster sampling. It also gives the lower bound on the model-based variances of best linear unbiased predictors of finite population totals under certain classes of superpopulation models.

 

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