Results 141 to 150 of about 289 (177)
Compounded wind gusts and maximum temperature via semiparametric copula in the risk assessments of power blackouts and air conditioning demands for major cities in Canada. [PDF]
Sci RepLatif S, Ouarda TBMJ.
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Vine copula based structural equation models
Computational Statistics & Data Analysisopenaire +2 more sources
Financial dependence analysis: applications of vine copulas [PDF]
Statistica Neerlandica, 2013 This paper features the application of a novel and recently developed method of statistical and mathematical analysis to the assessment of financial risk, namely regular vine copulas. Dependence modelling using copulas is a popular tool in financial applications but is usually applied to pairs of securities.
David E Allen +2 more
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Annual Review of Statistics and Its Application, 2022
With the availability of massive multivariate data comes a need to develop flexible multivariate distribution classes. The copula approach allows marginal models to be constructed for each variable separately and joined with a dependence structure characterized by a copula.
Claudia Czado, Thomas Nagler
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With the availability of massive multivariate data comes a need to develop flexible multivariate distribution classes. The copula approach allows marginal models to be constructed for each variable separately and joined with a dependence structure characterized by a copula.
Claudia Czado, Thomas Nagler
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Vine Copula Models with GLM and Sparsity
SSRN Electronic Journal, 2016Vine copula provides a flexible tool to capture asymmetry in modelling multivariate distributions. Nevertheless, its flexibility is achieved at the expense of exponentially increasing complexity of the model. To alleviate this issue, the simplifying assumption (SA) is commonly adapted in specific applications of vine copula models.
Dezhao Han, Ken Seng Tan, Chengguo Weng
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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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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
Model distances for vine copulas in high dimensions [PDF]
Statistics and Computing, 2017 Vine copulas are a flexible class of dependence models consisting of bivariate building blocks and have proven to be particularly useful in high dimensions. Classical model distance measures require multivariate integration and thus suffer from the curse of dimensionality.
Matthias Killiches +2 more
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Vine Copulas for Imputation of Monotone Non‐response
International Statistical Review, 2018SummaryMonotone patterns of non‐response may occur in longitudinal studies. When the measured variables are dependent, it is beneficial to use their joint statistical model to impute the missing values. We propose to use vine copulas to factorise the density of the observed variables into a cascade of bivariate copulas that yield a flexible model of ...
Caren Hasler +2 more
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