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基于排序集抽样的坎巴尼斯型二元均匀分布的参数估计

Parameter estimation of Cambanis-type bivariate uniform distribution with Ranked Set Sampling.

作者信息

Koshti Rohan D, Kamalja Kirtee K

机构信息

Department of Statistics, School of Mathematical Sciences, Kavayitri Bahinabai Chaudhari North Maharashtra University, Jalgaon, India.

出版信息

J Appl Stat. 2020 Jan 7;48(1):61-83. doi: 10.1080/02664763.2019.1709808. eCollection 2021.

Abstract

The concept of ranked set sampling (RSS) is applicable whenever ranking on a set of sampling units can be done easily using a judgment method or based on an auxiliary variable. In this paper, we consider a study variable correlated with the auxiliary variable and use it to rank the sampling units. Further is assumed to have Cambanis-type bivariate uniform (CTBU) distribution. We obtain an unbiased estimator of a scale parameter associated with the study variable based on different RSS schemes. We perform the efficiency comparison of the proposed estimators numerically. We present the trends in the efficiency performance of estimators under various RSS schemes with respect to parameters through line and surface plots. Further, we develop a Matlab function to simulate data from CTBU distribution and present the performance of proposed estimators through a simulation study. The results developed are implemented to real-life data also.

摘要

只要能使用判断方法或基于辅助变量轻松地对一组抽样单元进行排序,排序集抽样(RSS)的概念就适用。在本文中,我们考虑一个与辅助变量相关的研究变量,并用它对抽样单元进行排序。进一步假设该变量具有坎巴尼斯型二元均匀(CTBU)分布。我们基于不同的RSS方案获得了与研究变量相关的尺度参数的无偏估计量。我们对所提出的估计量进行了数值效率比较。我们通过线图和曲面图展示了各种RSS方案下估计量相对于参数的效率性能趋势。此外,我们开发了一个Matlab函数来模拟来自CTBU分布的数据,并通过模拟研究展示所提出估计量的性能。所得到的结果也应用于实际数据。

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