基于可选随机响应模型的非敏感辅助信息敏感变量有限总体均值的加性比型指数估计

IF 0.6 4区 数学 Q4 STATISTICS & PROBABILITY Brazilian Journal of Probability and Statistics Pub Date : 2022-09-01 DOI:10.1214/22-bjps535
L. Grover, Amanpreet Kaur
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引用次数: 0

摘要

摘要在抽样调查中适当地使用辅助信息可以提高感兴趣参数估计器的效率。本文利用非敏感辅助变量的已知信息,提出了一种基于可选随机响应模型的敏感研究变量总体均值的指数型估计。推导了该估计器的偏差和均方误差(MSE)的表达式,直至一阶近似。对于所提出的估计器,从理论上和数值上与现有估计器进行了效率比较。研究结果表明,即使辅助变量与研究变量之间的相关性很小,我们提出的估计量也比基于相同可选随机响应模型的现有估计量表现得更好。为了支持得到的结果,我们还使用仿真技术研究了所提出的指数估计器的性能。
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Additive ratio type exponential estimator of finite population mean of sensitive variable using non-sensitive auxiliary information based on optional randomized response model
Abstract. The appropriate use of auxiliary information in sample surveys increases the efficiency of estimator for parameter of interest. In this paper, we have proposed an exponential type estimator for the population mean of a sensitive study variable based on an optional randomized response model by using the known information on a non-sensitive auxiliary variable. Expressions for the bias and the mean square error (MSE) of the proposed estimator are derived, up to first order of approximation. For this proposed estimator, efficiency comparisons with the existing estimators have been carried out both theoretically and numerically. It has been shown that our proposed estimator perform better than the existing estimators based on the same optional randomized response model even for the small correlation between auxiliary variable and study variable. To support the results obtained,we have also studied the performance of the proposed exponential estimator using simulation technique.
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来源期刊
CiteScore
1.60
自引率
10.00%
发文量
30
审稿时长
>12 weeks
期刊介绍: The Brazilian Journal of Probability and Statistics aims to publish high quality research papers in applied probability, applied statistics, computational statistics, mathematical statistics, probability theory and stochastic processes. More specifically, the following types of contributions will be considered: (i) Original articles dealing with methodological developments, comparison of competing techniques or their computational aspects. (ii) Original articles developing theoretical results. (iii) Articles that contain novel applications of existing methodologies to practical problems. For these papers the focus is in the importance and originality of the applied problem, as well as, applications of the best available methodologies to solve it. (iv) Survey articles containing a thorough coverage of topics of broad interest to probability and statistics. The journal will occasionally publish book reviews, invited papers and essays on the teaching of statistics.
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