偏条件和平均条件肯德尔τ的研究

IF 0.6 Q4 STATISTICS & PROBABILITY Dependence Modeling Pub Date : 2021-01-01 DOI:10.1515/demo-2021-0104
I. Gijbels, Margot Matterne
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引用次数: 3

摘要

摘要当人们对研究条件依赖性,更确切地说是条件依赖性的强度感兴趣时,可能需要对条件随机向量进行某种平均。在这种情况下可以使用的平均度量的例子是平均条件肯德尔τ和部分肯德尔τ。众所周知,这些措施在总体上有所不同。一些统计测试是基于这些平均度量的,更好地了解这些度量是很重要的。本文的目的是对这两种平均测量的可能差异进行定量研究,并确定它们一致的充分条件。这两项措施都是在两个相当普遍的背景下进行研究的。在每种情况下,都建立了理论结果,并给出了几个例证。
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Study of partial and average conditional Kendall’s tau
Abstract When the interest is in studying conditional dependencies, and more precisely the strength of conditional dependencies, some kind of averaging over the conditioning random vector may be needed. Examples of average measures that can serve in this context are the average conditional Kendall’s tau and partial Kendall’s tau. It is known that these measures differ in general. Some statistical tests are based on these average measures, and a better knowledge of them is of importance. The aim of this paper is to provide a quantitative study of the possible differences of these two average measures, and to establish su˚cient conditions under which they coincide. Both measures are studied in two fairly general settings. In each setting theoretical results are established as well as several illustrative examples given.
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来源期刊
Dependence Modeling
Dependence Modeling STATISTICS & PROBABILITY-
CiteScore
1.00
自引率
0.00%
发文量
18
审稿时长
12 weeks
期刊介绍: The journal Dependence Modeling aims at providing a medium for exchanging results and ideas in the area of multivariate dependence modeling. It is an open access fully peer-reviewed journal providing the readers with free, instant, and permanent access to all content worldwide. Dependence Modeling is listed by Web of Science (Emerging Sources Citation Index), Scopus, MathSciNet and Zentralblatt Math. The journal presents different types of articles: -"Research Articles" on fundamental theoretical aspects, as well as on significant applications in science, engineering, economics, finance, insurance and other fields. -"Review Articles" which present the existing literature on the specific topic from new perspectives. -"Interview articles" limited to two papers per year, covering interviews with milestone personalities in the field of Dependence Modeling. The journal topics include (but are not limited to):  -Copula methods -Multivariate distributions -Estimation and goodness-of-fit tests -Measures of association -Quantitative risk management -Risk measures and stochastic orders -Time series -Environmental sciences -Computational methods and software -Extreme-value theory -Limit laws -Mass Transportations
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