Results 91 to 100 of about 4,366 (211)

General Multivariate Dependence using Associated Copulas

Revstat Statistical Journal, 2016
This paper studies the general multivariate dependence and tail dependence of a random vector. We analyse the dependence of variables going up or down, covering the 2 d orthants of dimension d and accounting for non-positive dependence.
Yuri Salazar Flores
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Archimedean Copulas-Based Estimation under One-Parameter Distributions in Coherent Systems

Mathematics
In the present work we provide a signature-based framework for delivering the estimated mean lifetime along with the variance of the continuous distribution of a coherent system consisting of exchangeable components.
Ioannis S. Triantafyllou
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Nested Archimedean copulas: a new class of nonparametric tree structure estimators

, 2014
Any nested Archimedean copula is defined starting from a rooted phylogenetic tree, for which a new class of nonparametric estimators is presented. An estimator from this new class relies on a two-step procedure where first a binary tree is built and ...
Uyttendaele, Nathan
core  

Copula estimation for nonsynchronous financial data

, 2020
Copula is a powerful tool to model multivariate data. We propose the modelling of intraday financial returns of multiple assets through copula. The problem originates due to the asynchronous nature of intraday financial data.
Chakrabarti, Arnab, Sen, Rituparna
core  

From Archimedean to Liouville copulas

Journal of Multivariate Analysis, 2010
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
McNeil, Alexander J., Nešlehová, Johanna   +1 more
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Copula–entropy theory for multivariate stochastic modeling in water engineering

Geoscience Letters, 2018
The copula–entropy theory combines the entropy theory and the copula theory. The entropy theory has been extensively applied to derive the most probable univariate distribution subject to specified constraints by applying the principle of maximum entropy.
Vijay P. Singh, Lan Zhang
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Lower Tail Dependence for Archimedean Copulas: Characterizations and Pitfalls [PDF]

Tail dependence copulas provide a natural perspective from which one can study the dependence in the tail of a multivariate distribution.For Archimedean copulas with continuously differentiable generators, regular variation of the generator near the ...
Charpentier, A., Segers, J.J.J.
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A copula-based approach to aggregation functions [PDF]

This paper presents the role of copula functions in the theory of aggregation operators and an axiomatic characterization of Archimedean aggregation functions.
Maddalena Manzi, Marta Cardin
core  

Likelihood inference for Archimedean copulas

, 2011
Explicit functional forms for the generator derivatives of well-known one-parameter Archimedean copulas are derived. These derivatives are essential for likelihood inference as they appear in the copula density, conditional distribution functions, or the Kendall distribution function.
Hofert, Marius, Mächler, Martin, McNeil, Alexander J.   +2 more
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Bayesian Nonparametric Mixtures of Archimedean Copulas

Journal of Agricultural, Biological and Environmental Statistics
Copula-based dependence modeling often relies on parametric formulations. This is mathematically convenient, but can be statistically inefficient when the parametric families are not suitable for the data and model in focus. A Bayesian nonparametric mixture of Archimedean copulas is introduced to increase the flexibility of copula-based dependence ...
Pan, Ruyi, Nieto-Barajas, Luis E., Craiu, Radu V.   +2 more
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