文章基本信息

标题：Mixture Ratio Estimators Using Multi-Auxiliary Variables and Attributes for Two-Phase Sampling
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作者：Paul Mwangi Waweru , John Kung’u , James Kahiri
期刊名称：Open Journal of Statistics
印刷版ISSN：2161-718X
电子版ISSN：2161-7198
出版年度：2014
卷号：04
期号：09
页码：776-788
DOI：10.4236/ojs.2014.49073
语种：English
出版社：Scientific Research Publishing
摘要：In this paper, we have proposed three classes of mixture ratio estimators for estimating population mean by using information on auxiliary variables and attributes simultaneously in two-phase sampling under full, partial and no information cases and analyzed the properties of the estimators. A simulated study was carried out to compare the performance of the proposed estimators with the existing estimators of finite population mean. It has been found that the mixture ratio estimator in full information case using multiple auxiliary variables and attributes is more efficient than mean per unit, ratio estimator using one auxiliary variable and one attribute, ratio estimator using multiple auxiliary variable and multiple auxiliary attributes and mixture ratio estimators in both partial and no information case in two-phase sampling. A mixture ratio estimator in partial information case is more efficient than mixture ratio estimators in no information case.
关键词：Ratio Estimator; Multiple Auxiliary Variables; Multiple Auxiliary Attributes; Two-Phase Sampling; Bi-Serial Correlation Coefficient