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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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Model Selection Based on Residual Dependence Measure [PDF]
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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A subcopula based dependence measure [PDF]
Kybernetika, 2017 A dependence measure for arbitrary type pairs of random variables is proposed and analyzed, which in the particular case where both random variables are continuous turns out to be a concordance measure. Also, a sample version of the proposed dependence measure based on the empirical subcopula is provided, along with an R package to perform the ...
Erdely, Arturo
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Dependence measure for length-biased survival data using copulas [PDF]
Dependence Modeling, 2019 The linear correlation coefficient of Bravais-Pearson is considered a powerful indicator when the dependency relationship is linear and the error variate is normally distributed.
Bentoumi Rachid +2 more
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Continuous dependence results for set-valued measure differential problems [PDF]
Electronic Journal of Qualitative Theory of Differential Equations, 2015 We discuss existence and continuous dependence properties of solutions set of measure differential inclusions \begin{equation}\label{(1)} \begin{split} dx(t)& \in G(t, x(t)) d\mu(t),\\ x(0)& = x_0. \end{split} \end{equation} where $G \colon [0,1] \times \
Bianca Satco
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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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Ordinal pattern dependence as a multivariate dependence measure [PDF]
Journal of Multivariate Analysis, 2021 In this article, we show that the recently introduced ordinal pattern dependence fits into the axiomatic framework of general multivariate dependence measures, i.e., measures of dependence between two multivariate random objects. Furthermore, we consider multivariate generalizations of established univariate dependence measures like Kendall's $τ ...
Annika Betken +3 more
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Searching With Measurement Dependent Noise [PDF]
IEEE Transactions on Information Theory, 2014 Consider a target moving at a constant velocity on a unit-circumference circle, starting at an arbitrary location. To acquire the target, any region of the circle can be probed to obtain a noisy measurement of the target's presence, where the noise level increases with the size of the probed region.
Yonatan Kaspi +2 more
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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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