A predictive estimator of finite population proportion despite missing data

被引：1

作者：

Rueda, M. ^{[1
]}

Gonzalez, S. ^{[1
]}

Arcos, A. ^{[1
]}

机构：

[1] Univ Granada, Dept Stat & OR, E-18071 Granada, Spain

来源：

APPLIED MATHEMATICS AND COMPUTATION | 2014年 / 233卷

关键词：

Superpopulation models; Missing data; Auxiliary information; AUXILIARY ATTRIBUTES; RANDOM NONRESPONSE; INFORMATION; VARIANCE; RATIO; REGRESSION; MODEL;

D O I：

10.1016/j.amc.2014.01.128

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

This paper considers the problem of estimating a finite population proportion when there are missing values. The prediction approach is used to define a new estimator that presents desirable efficiency properties. Simulation studies are considered to evaluate the performance of the proposed estimator via empirical relative bias and empirical relative efficiency, and favourable results are achieved. (C) 2014 Elsevier Inc. All rights reserved.

引用

页码：1 / 9

页数：9

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