Results 91 to 100 of about 289 (177)
Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 2015 The article points out the possibilities of using static D-Vine copula ARMA-GARCH model for estimation of 1 day ahead market Value at Risk. For the illustration we use data of the four companies listed on Prague Stock Exchange in range from 2010 to 2014.
Václav Klepáč, David Hampel
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Learning Vine Copula Models for Synthetic Data Generation
Proceedings of the AAAI Conference on Artificial Intelligence, 2019 A vine copula model is a flexible high-dimensional dependence model which uses only bivariate building blocks. However, the number of possible configurations of a vine copula grows exponentially as the number of variables increases, making model selection a major challenge in development.
Yi Sun +2 more
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Pruning and Truncating the Mixture R-Vine Model Using the Mixture Weight
Journal of Probability and StatisticsVine copula mixture models are highly flexible and can handle complex hidden dependencies among variables without restricting the parametric shape of the margins or the type of dependency structure.
Fadhah Alanazi
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Contributions to Vine-Copula Modeling
, 2022 Regular vine-copula models (R-vines) are a powerful statistical tool for modeling thedependence structure of multivariate distribution functions. In particular, they allow modelingdierent types of dependencies among random variables independently of their marginaldistributions, which is deemed the most valued characteristic of these models.
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Truncation Mixture R-Vine Copulas
, 2021 Uncovering hidden mixture correlation among variables have been investigating in the literature using mixture R-vine copula models. These models are hierarchical in nature. They provides a huge flexibility for modelling multivariate data. As the dimensions increases, the number of the model parameters that need to be estimated is increased dramatically,
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Copula Modeling of COVID-19 Excess Mortality
RisksCOVID-19’s effects on mortality are hard to quantify. Issues with attribution can cause problems with resulting conclusions. Analyzing excess mortality addresses this concern and allows for the analysis of broader effects of the pandemic.
Jonas Asplund, Arkady Shemyakin
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A Bivariate Copula–Driven Multi-State Model for Statistical Analysis in Medical Research
MathematicsWe develop and evaluate a copula-based multistate model for illness–death processes with dependent transition times. The framework couples Cox proportional hazards models for the marginal transition intensities with Archimedean copulas to capture ...
Hugo Brango +2 more
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Value-at-Risk with Vine Copulas
, 2023 Especially when considering a portfolio with multiple assets the dependence structure in-between them is crucial regarding the grade of diversification and risk assessment. Models which consist of the multivariate normal distribution are popular because of their simplicity and fast calculation time.
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An econometric Study for Vine Copulas
, 2011 We present a new recursive algorithm to construct vine copulas based on an underlying tree structure. This new structure is interesting to compute multivariate distributions for dependent random variables. We proove the asymptotic normality of the vine copula parameter estimator and show that all vine copula parameter estimators have comparable ...
Guegan, Dominique, Maugis, Pierre-André
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Vine Copula-Based Outage Analysis for Fluid Antenna RIS-NOMA Systems Over Nakagami-
IEEE Open Journal of the Communications SocietyOutage performance in multi-port fluid antenna (FA) systems is governed by the tail dependence between correlated ports, which Gaussian-copula models cannot capture.
Mohammad Al Bataineh, Zaid Albataineh
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