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We propose R\'enyi inaccuracy measure based on multivariate copula and multivariate survival copula, respectively dubbed as multivariate cumulative copula R\'enyi inaccuracy measure and multivariate survival copula R\'enyi inaccuracy…

Statistics Theory · Mathematics 2025-02-25 Shital Saha , Suchandan Kayal

Multivariate datasets are common in various real-world applications. Recently, copulas have received significant attention for modeling dependencies among random variables. A copula-based information measure is required to quantify the…

Methodology · Statistics 2024-08-06 Mohd. Arshad , Swaroop Georgy Zachariah , Ashok Kumar Pathak

This study outlines a comprehensive methodology utilizing copulas to discern inconsistencies in the behavior exhibited by pairs of financial assets. It introduces a robust approach to establishing the interrelationship between the returns…

Computational Finance · Quantitative Finance 2023-12-05 Alexander Shulzhenko

Building upon earlier work in which axioms were formulated for multivariate measures of concordance, we examine properties of such measures. In particular, we examine the relations between the measure of concordance of an $n$-copula and the…

Probability · Mathematics 2016-10-18 M. D. Taylor

For the analysis of clustered survival data, two different types of models that take the association into account, are commonly used: frailty models and copula models. Frailty models assume that conditional on a frailty term for each…

Methodology · Statistics 2014-01-10 Leen Prenen , Roel Braekers , Luc Duchateau

In this paper, we revisit the notion of partial copula, originally introduced to test conditional independence, highlighting its capability to represent the dependence between two random variables after removing their dependence with a…

Methodology · Statistics 2026-05-26 Vinícius Litvinoff Justus , Felipe Fontana Vieira

We discuss the connection between information and copula theories by showing that a copula can be employed to decompose the information content of a multivariate distribution into marginal and dependence components, with the latter…

Statistical Finance · Quantitative Finance 2011-10-26 Rafael S. Calsaverini , Renato Vicente

This paper addresses the problem of quantification and propagation of uncertainties associated with dependence modeling when data for characterizing probability models are limited. Practically, the system inputs are often assumed to be…

Computation · Statistics 2020-04-14 Jiaxin Zhang , Michael D. Shields

We propose the extension of Fr\'{e}chet-Hoeffding copula bounds for circular data. The copula is a powerful tool for describing the dependency of random variables. In two dimensions, the Fr\'{e}chet-Hoeffding upper (lower) bound indicates…

Statistics Theory · Mathematics 2023-11-17 Hiroaki Ogata

A new index based on empirical copulas, termed the Copula Statistic (CoS), is introduced for assessing the strength of multivariate dependence and for testing statistical independence. New properties of the copulas are proved. They allow us…

Statistics Theory · Mathematics 2016-12-22 Mohsen Ben Hassine , Lamine Mili , Kiran Karra

The present article studies survival analytic aspects of semiparametric copula dependence models with arbitrary univariate marginals. The underlying survival functions admit a representation via exponent measures which have an…

Statistics Theory · Mathematics 2014-09-25 Jens Bendel , Dennis Dobler , Arnold Janssen

A new class of copulas based on order statistics was introduced by Baker (2008). Here, further properties of the bivariate and multivariate copulas are described, such as that of likelihood ratio dominance (LRD), and further bivariate…

Methodology · Statistics 2014-12-03 Rose Baker

The paper presents a new copula based method for measuring dependence between random variables. Our approach extends the Maximum Mean Discrepancy to the copula of the joint distribution. We prove that this approach has several advantageous…

Machine Learning · Computer Science 2019-08-15 Barnabas Poczos , Zoubin Ghahramani , Jeff Schneider

Copulas are mathematical objects that fully capture the dependence structure among random variables and hence, offer a great flexibility in building multivariate stochastic models. In statistics, a copula is used as a general way of…

Methodology · Statistics 2013-10-01 Abhik Ghosh , Aritra Chakravorty

Following the theory of information measures based on the cumulative distribution function, we propose the fractional generalized cumulative entropy, and its dynamic version. These entropies are particularly suitable to deal with…

Probability · Mathematics 2021-06-30 Antonio Di Crescenzo , Suchandan Kayal , Alessandra Meoli

We propose a new multivariate dependency measure. It is obtained by considering a Gaussian kernel based distance between the copula transform of the given d-dimensional distribution and the uniform copula and then appropriately normalizing…

Statistics Theory · Mathematics 2019-11-12 Angshuman Roy , Alok Goswami , C. A. Murthy

Zero-inflated continuous data ubiquitously appear in many fields, in which lots of exactly zero-valued data are observed while others distribute continuously. Due to the mixed structure of discreteness and continuity in its distribution,…

Methodology · Statistics 2024-10-28 Keita Hamamoto

Following our previous work on copula-based nonsymmetric bivariate dependence measures, we propose a new set of conditions on nonsymmetric multivariate dependence measures which characterize both independence and complete dependence of one…

Methodology · Statistics 2015-12-04 Hui Li

Over the last couple of decades, several copula based methods have been proposed in the literature to test for the independence among several random variables. But these existing tests are not invariant under monotone transformations of the…

Statistics Theory · Mathematics 2019-11-15 Angshuman Roy , Anil Ghosh , Alok Goswami , C. A. Murthy

Fractional cumulative residual inaccuracy (FCRI) measure allows to determine regions of discrepancy between systems, depending on their respective fractional and chaotic map parameters. Most of the theoretical results and applications…

Applications · Statistics 2025-11-25 Iona Ann Sebastian , S. M. Sunoj
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