On concomitants of order statistics arising from the extended Farlie–Gumbel–Morgenstern bivariate logistic distribution and its application in estimation

Q Mathematics

Statistical Methodology Pub Date : 2015-07-01 DOI:10.1016/j.stamet.2015.02.002

Anne Philip, P. Yageen Thomas

引用次数: 10

Abstract

In this paper, we consider concomitants of order statistics arising from the extended Farlie–Gumbel–Morgenstern bivariate logistic distribution and develop its distribution theory. Using ranked set sample obtained from the above distribution, unbiased estimators of the parameters associated with the study variate involved in it are generated. The best linear unbiased estimators (BLUEs) based on observations in the ranked set sample of those parameters as well have been derived. The efficiencies of the BLUEs relative to the respective unbiased estimators generated also have been evaluated.

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扩展Farlie-Gumbel-Morgenstern双变量logistic分布引起的有序统计量的伴随性及其在估计中的应用

本文考虑了广义Farlie-Gumbel-Morgenstern二元logistic分布所产生的序统计量的伴随性，并发展了其分布理论。使用从上述分布中获得的排序集样本，生成与其中涉及的研究变量相关的参数的无偏估计量。基于这些参数的排序集样本的观测结果，也得到了最佳的线性无偏估计(BLUEs)。还评估了blue相对于生成的各自无偏估计器的效率。

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

Statistical Methodology STATISTICS & PROBABILITY-

CiteScore

0.59

自引率

0.00%

发文量

期刊介绍： Statistical Methodology aims to publish articles of high quality reflecting the varied facets of contemporary statistical theory as well as of significant applications. In addition to helping to stimulate research, the journal intends to bring about interactions among statisticians and scientists in other disciplines broadly interested in statistical methodology. The journal focuses on traditional areas such as statistical inference, multivariate analysis, design of experiments, sampling theory, regression analysis, re-sampling methods, time series, nonparametric statistics, etc., and also gives special emphasis to established as well as emerging applied areas.