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Two Measures of Dependence [PDF]
Entropy, 2019 Two families of dependence measures between random variables are introduced. They are based on the Rényi divergence of order α and the relative
Amos Lapidoth, Christoph Pfister
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Extending Hilbert–Schmidt Independence Criterion for Testing Conditional Independence
Entropy, 2023 The Conditional Independence (CI) test is a fundamental problem in statistics. Many nonparametric CI tests have been developed, but a common challenge exists: the current methods perform poorly with a high-dimensional conditioning set.
Bingyuan Zhang, Joe Suzuki
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Maximal asymmetry of bivariate copulas and consequences to measures of dependence
Dependence Modeling, 2022 In this article, we focus on copulas underlying maximal non-exchangeable pairs (X,Y)\left(X,Y) of continuous random variables X,YX,Y either in the sense of the uniform metric d∞{d}_{\infty } or the conditioning-based metrics Dp{D}_{p}, and analyze their ...
Griessenberger Florian +1 more
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Model Selection Based on Residual Dependence Measure
IEEE Access, 2023 Choosing the most suitable model from a set of models is crucial. Based on the assumption that the noise and independent variables in the model are independent, the degree of fit of the model was determined by studying the correlation between the ...
Linfeng Lyu, Yiming Ding, Yuan Wan
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Dependence Modeling, 2023 Working with shuffles, we establish a close link between Kendall’s τ\tau , the so-called length measure, and the surface area of bivariate copulas and derive some consequences.
Sánchez Juan Fernández +1 more
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A Note on the Maximum Difference Between Schweizer and Wolff's $\sigma$ and the Absolute Value of Spearman's $\rho$ [PDF]
Transactions on Fuzzy Sets and Systems, 2022 In this note we correct an error on the possible maximum difference between the (measure of dependence) Schweizer and Wolff's sigma and the absolute value of the (measure of concordance) Spearman's rho given in [B. Schweizer and E. F.
Manuel Ubeda-Flores
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Plug-in Estimation of Dependence Characteristics of Archimedean Copula via Bézier Curve
Revstat Statistical Journal, 2023 This article introduces measurement of the dependence between variables with a dependence structure defined by Archimedean copulas. The estimation of the dependence measure, such as Kendall’s tau as well as the lower and upper tail dependence, is ...
Selim Orhun Susam +1 more
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Hidden Markov Models as a Tool for the Assessment of Dependence of Phenomena of Economic Nature
Acta Universitatis Lodziensis. Folia Oeconomica, 2018 The assessment of dependence between time series is a common dilemma, which is often solved by the use of the Pearson’s correlation coefficient. Unfortunately, sometimes, the results may be highly misleading.
Michał Bernardelli
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Mutual Information and Dynamic Measure of Inaccuracy between Past Lifetime Distributions [PDF]
The Egyptian Statistical Journal, 2010 The mutual information is a measure of the dependence of two random variables. We propose an extension of this notion to measure the dependence between the inactivity lifetimes of two systems, given that both systems have failure at time t.
Mervat Mahdy Ramadan Mahdy
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A Class of Association Measures for Categorical Variables Based on Weighted Minkowski Distance
Entropy, 2019 Measuring and testing association between categorical variables is one of the long-standing problems in multivariate statistics. In this paper, I define a broad class of association measures for categorical variables based on weighted Minkowski distance.
Qingyang Zhang
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