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Vine Copula-Based Classifiers with Applications
Journal of ClassificationAbstract The vine pair-copula construction can be used to fit flexible non-Gaussian multivariate distributions to a mix of continuous and discrete variables. With multiple classes, fitting univariate distributions and a vine to each class lead to posterior probabilities over classes that can be used for discriminant analysis.
Özge Şahin, Harry Joe
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Modeling vine-production function: An approach based on Vine Copula
Physica A: Statistical Mechanics and its Applications, 2019zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Constantino, Michel +4 more
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On copula-based collective risk models: from elliptical copulas to vine copulas
Scandinavian Actuarial Journal, 2020Several collective risk models have recently been proposed by relaxing the widely used but controversial assumption of independence between claim frequency and severity.
Rosy Oh, Jae Youn Ahn, Woojoo Lee
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Energy Engineering
: To adapt to the uncertainty of new energy, increase new energy consumption, and reduce carbon emissions, a high-voltage distribution network energy storage planning model based on robustness-oriented planning and distributed new energy consumption is ...
Jiaqing Wang +3 more
semanticscholar +1 more source
: To adapt to the uncertainty of new energy, increase new energy consumption, and reduce carbon emissions, a high-voltage distribution network energy storage planning model based on robustness-oriented planning and distributed new energy consumption is ...
Jiaqing Wang +3 more
semanticscholar +1 more source
Robust Portfolio Selection Using Vine Copulas
SSRN Electronic Journal, 2020Portfolio optimization problems involving Conditional Value-at-Risk (CVaR) are often computationally intractable and require complete information about the distribution of returns, which is rarely available in practice. These difficulties are compounded when the portfolio contains a lot of assets.
Yingwei Han, Ping Li
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International Conference on Artificial Intelligence and Statistics
We propose TVineSynth, a vine copula based synthetic tabular data generator, which is designed to balance privacy and utility, using the vine tree structure and its truncation to do the trade-off.
Elisabeth Griesbauer +3 more
semanticscholar +1 more source
We propose TVineSynth, a vine copula based synthetic tabular data generator, which is designed to balance privacy and utility, using the vine tree structure and its truncation to do the trade-off.
Elisabeth Griesbauer +3 more
semanticscholar +1 more source
2013
Vine copula models have proven themselves as a very flexible class of multivariate copula models with regard to symmetry and tail dependence for pairs of variables. The full specification of a vine model requires the choice of a vine tree structure, the copula families for each pair copula term and their corresponding parameters.
Claudia Czado +2 more
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Vine copula models have proven themselves as a very flexible class of multivariate copula models with regard to symmetry and tail dependence for pairs of variables. The full specification of a vine model requires the choice of a vine tree structure, the copula families for each pair copula term and their corresponding parameters.
Claudia Czado +2 more
openaire +1 more source
Vine copula MFPCA residual control chart for sparse multivariate functional data
Communications in statistics. Simulation and computationWe introduce a multivariate functional principal component analysis (MFPCA) residual control chart for multivariate functional data. Our method utilizes the vine copula technique and is applied to high-frequency financial data.
Jong-Min Kim, Il Do Ha
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Gaussian Process with Vine Copula-Based Context Modeling for Contextual Multi-Armed Bandits
MathematicsWe propose a novel contextual multi-armed bandit (CMAB) framework that integrates copula-based context generation with Gaussian Process (GP) regression for reward modeling, addressing complex dependency structures and uncertainty in sequential decision ...
Jong‐Min Kim
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Atmosphere
Accurate modelling of near surface wind speeds is essential for robust resource assessment, turbine design, and grid integration. This study presents a unified framework comparing four candidate marginal distributions—Weibull, Gamma, Lognormal, and ...
Khaled Haddad
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Accurate modelling of near surface wind speeds is essential for robust resource assessment, turbine design, and grid integration. This study presents a unified framework comparing four candidate marginal distributions—Weibull, Gamma, Lognormal, and ...
Khaled Haddad
semanticscholar +1 more source