ON THE CONSISTENCY BETWEEN MODEL-BASED AND DESIGN-BASED ESTIMATORS IN SURVEY SAMPLING

被引:5
|
作者
GHOSH, M
SINHA, BK
机构
[1] UNIV FLORIDA, 486 LITTLE HALL, GAINESVILLE, FL 32611 USA
[2] INDIAN STAT INST, CALCUTTA 700035, W BENGAL, INDIA
基金
美国国家科学基金会;
关键词
based estimators; design; empirical Bayes; Finite population sampling; hierarchical Bayes; Horvitz-Thompson estimator; model based estimators; pps sampling; ratio estimator; stepwise Bayes;
D O I
10.1080/03610929008830226
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
In finite population sampling, often a distinction is made between model- and design-based estimators of the parameters of interest (like the population total, population variance, etc.). The model-based estimators depend on the (known) parameters of the model, while the design-based estimators depend on the (known) selection probabilities of the different units in the population. It is shown in this paper that the two approaches are not necessarily incompatible, and indeed can often lead to the same estimator. Our ideas are illustrated with the Horvitz-Thompson, and the generalized Horvitz-Thompson estimator. These estimators are identified as hierarchical. © 1990, Taylor & Francis Group, LLC. All rights reserved.
引用
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页码:689 / 702
页数:14
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