随机无响应条件下有限总体方差的两个新估计量及其应用

Q4 Mathematics
Alisha Mittal, M. Kumar
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引用次数: 1

摘要

本文试图通过提出两个估计量来研究无响应情况下无替换简单随机抽样(SRSWOR)中有限总体方差的估计。在辅助信息可用性和不可用性的基础上,提出了两种估计量(对偶-比率和比率兼对偶-比率型)。还研究了所提出的估计量的偏差和均方误差等性质,直至一阶近似。将所提出的估计量与现有的一些估计量进行了比较,并进行了相互比较。基于蔬菜作物数据和模拟数据进行了实证研究,以找出最佳估计量。研究表明,在这两种估计量中,比率兼对偶与比率型估计量的性能要好于对偶与比率估计量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Two new estimators of finite population variance under random non-response: An application
In this paper, an attempt has been made to study the estimation of finite population variance in simple random sampling without replacement (SRSWOR) in presence of non-response by proposing two estimators. The two estimators (dual to ratio and ratio cum dual to ratio type) have been proposed on the basis of availability and non-availability of auxiliary information. The properties such as bias and mean square error of the proposed estimators have also been studied up to first order of approximation. The proposed estimators are compared with some existing estimators and are also mutually compared. An empirical study, based on both vegetable crop data and simulated data, has been performed to find out the best estimator. It has been seen that out of the two proposed estimators, the ratio cum dual to ratio type estimator performed better than dual to ratio estimator.
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来源期刊
Model Assisted Statistics and Applications
Model Assisted Statistics and Applications Mathematics-Applied Mathematics
CiteScore
1.00
自引率
0.00%
发文量
26
期刊介绍: Model Assisted Statistics and Applications is a peer reviewed international journal. Model Assisted Statistics means an improvement of inference and analysis by use of correlated information, or an underlying theoretical or design model. This might be the design, adjustment, estimation, or analytical phase of statistical project. This information may be survey generated or coming from an independent source. Original papers in the field of sampling theory, econometrics, time-series, design of experiments, and multivariate analysis will be preferred. Papers of both applied and theoretical topics are acceptable.
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