Results 41 to 50 of about 489 (106)
On the asymptotic covariance of the multivariate empirical copula process
Dependence Modeling, 2019 Genest and Segers (2010) gave conditions under which the empirical copula process associated with a random sample from a bivariate continuous distribution has a smaller asymptotic covariance than the standard empirical process based on a random sample ...
Genest Christian +2 more
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Multivariate Measures of Concordance for Copulas and their Marginals
, 2010 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 measures of ...
Dolati +11 more
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On bivariate Archimedean copulas with fractal support
Dependence ModelingDue to their simple analytic form (bivariate) Archimedean copulas are usually viewed as very smooth and handy objects, which should distribute mass in a fairly regular and certainly not in a pathological way. Building upon recently established results on
Sánchez Juan Fernández +1 more
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Copula-Based Dependence Measures For Piecewise Monotonicity
Dependence Modeling, 2017 The aim of the present paper is to develop and examine association coefficients which can be helpfully applied in the framework of regression analysis.
Liebscher Eckhard
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Asymptotic study of canonical correlation analysis: from matrix and analytic approach to operator and tensor approach [PDF]
, 2003 Asymptotic study of canonical correlation analysis gives the opportunity to present the different steps of an asymptotic study and to show the interest of an operator and tensor approach of multidimensional asymptotic statistics rather than the classical,
Fine, Jeanne
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New copulas based on general partitions-of-unity (part III) — the continuous case
Dependence Modeling, 2019 In this paper we discuss a natural extension of infinite discrete partition-of-unity copulas which were recently introduced in the literature to continuous partition of copulas with possible applications in risk management and other fields.
Pfeifer Dietmar +3 more
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Bivariate copulas defined from matrices [PDF]
, 2013 We propose a semiparametric family of copulas based on a set of orthonormal functions and a matrix. This new copula permits to reach values of Spearman's Rho arbitrarily close to one without introducing a singular component.
Amblard, Cécile +2 more
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Sparse permutation invariant covariance estimation
, 2007 The paper proposes a method for constructing a sparse estimator for the inverse covariance (concentration) matrix in high-dimensional settings. The estimator uses a penalized normal likelihood approach and forces sparsity by using a lasso-type penalty ...
Bickel, Peter J. +3 more
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Dependence Modeling, 2019 We study nonparametric estimators of conditional Kendall’s tau, a measure of concordance between two random variables given some covariates. We prove non-asymptotic pointwise and uniform bounds, that hold with high probabilities.
Derumigny Alexis, Fermanian Jean-David
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Dependence properties of bivariate copula families
Dependence ModelingMotivated by recently investigated results on dependence measures and robust risk models, this article provides an overview of dependence properties of many well known bivariate copula families, where the focus is on the Schur order for conditional ...
Ansari Jonathan, Rockel Marcus
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