An efficient exponential estimator of the mean under stratified random sampling

IF 1.4 3区社会学 Q3 DEMOGRAPHY

Mathematical Population Studies Pub Date : 2020-06-16 DOI:10.1080/08898480.2020.1767420

T. Zaman

引用次数: 27

Abstract

ABSTRACT Stratification of population is a probability sampling design used to increase the precision of estimation. An efficient exponential ratio estimator allows estimating the population mean in stratified random sampling using an auxiliary variable. Its expected bias, expected mean square error, and minimum mean square error are expressed. The conditions for which the estimator is more efficient are obtained. The proposed estimators under stratified random sampling have a lower mean square error than the ratio and the exponential estimators.

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分层随机抽样下均值的有效指数估计

人口分层是一种概率抽样设计，用于提高估计精度。有效的指数比率估计器允许使用辅助变量在分层随机抽样中估计总体平均值。表达了它的期望偏差、期望均方误差和最小均方误差。获得了估计器更有效的条件。在分层随机抽样下，所提出的估计量具有比比率和指数估计量更低的均方误差。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Mathematical Population Studies 数学-数学跨学科应用

CiteScore

3.20

自引率

11.10%

发文量

审稿时长

>12 weeks

期刊介绍： Mathematical Population Studies publishes carefully selected research papers in the mathematical and statistical study of populations. The journal is strongly interdisciplinary and invites contributions by mathematicians, demographers, (bio)statisticians, sociologists, economists, biologists, epidemiologists, actuaries, geographers, and others who are interested in the mathematical formulation of population-related questions. The scope covers both theoretical and empirical work. Manuscripts should be sent to Manuscript central for review. The editor-in-chief has final say on the suitability for publication.