Improved unbiased estimators in adaptive cluster sampling

被引：18

作者：

Dryver, AL ^{[1
]}

Thompson, SK ^{[1
]}

机构：

[1] Penn State Univ, Dept Stat, University Pk, PA 16802 USA

来源：

JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY | 2005年 / 67卷

关键词：

adaptive sampling; design-unbiased estimation; Rao-Blackwell method;

D O I：

10.1111/j.1467-9868.2005.00493.x

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：

The usual design-unbiased estimators in adaptive cluster sampling are easy to compute but are not functions of the minimal sufficient statistic and hence can be improved. Improved unbiased estimators obtained by conditioning on sufficient statistics-not necessarily minimal-are described. First, estimators that are as easy to compute as the usual design-unbiased estimators are given. Estimators obtained by conditioning on the minimal sufficient statistic which are more difficult to compute are also discussed. Estimators are compared in examples.

引用

页码：157 / 166

页数：10

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