Tests for independence against regression and expectation dependence

IF 1.4 4区 数学 Q3 STATISTICS & PROBABILITY
Sudheesh K. Kattumannil, Deepesh Bhati, Isha Dewan
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引用次数: 0

Abstract

In this paper, we propose nonparametric tests based on U-statistics for testing independence against two different classes of alternatives: positive regression dependence and positive expectation dependence. We obtain the asymptotic distribution of the test statistics both under the null and the alternative hypothesis. An extensive Monte Carlo simulation study is done to assess the finite sample performance of the proposed tests. The test procedures are illustrated using two data sets.

Abstract Image

针对回归和期望依赖的独立性测试
在本文中,我们提出了基于u统计量的非参数检验,用于检验对两类不同选择的独立性:正回归依赖和正期望依赖。我们得到了零假设和备假设下检验统计量的渐近分布。进行了广泛的蒙特卡罗模拟研究,以评估所提出的测试的有限样本性能。使用两个数据集说明测试过程。
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
CiteScore
2.00
自引率
0.00%
发文量
39
审稿时长
6-12 weeks
期刊介绍: Annals of the Institute of Statistical Mathematics (AISM) aims to provide a forum for open communication among statisticians, and to contribute to the advancement of statistics as a science to enable humans to handle information in order to cope with uncertainties. It publishes high-quality papers that shed new light on the theoretical, computational and/or methodological aspects of statistical science. Emphasis is placed on (a) development of new methodologies motivated by real data, (b) development of unifying theories, and (c) analysis and improvement of existing methodologies and theories.
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