Results 91 to 100 of about 25,546 (258)
On approximating copulas by finite mixtures
, 2018 Copulas are now frequently used to approximate or estimate multivariate distributions because of their ability to take into account the multivariate dependence of the variables while controlling the approximation properties of the marginal densities ...
Khaled, Mohamad A., Kohn, Robert
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An objective Bayesian method for including parameter uncertainty in ensemble model output statistics
Quarterly Journal of the Royal Meteorological Society, EarlyView.Conventional model output statistics and ensemble model output statistics methods for calibrating ensemble forecasts lead to severe underestimation of the probabilities of ensemble extremes (in blue). This is because they ignore statistical parameter uncertainty.
Stephen Jewson +4 more
wiley +1 more source
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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Discrete copulas and quasi-copulas
, 2022 The thesis gives a brief introduction to two dimensional copulas and related functions. Firstly, we present copulas, their usage and according history. Furthermore, in the text we include some examples and visual representations for this purpose. Copulas are cumulative distribution functions defined on the unit square with marginal distributions which ...
openaire +1 more source
Quarterly Journal of the Royal Meteorological Society, EarlyView.The dual graph neural network (dualGNN), trained with a composite loss combining the energy score (ES) and variogram score (VS), consistently outperformed models optimized solely for ES or the continuous ranked probability score in the multivariate setting, as well as empirical copula approaches.
Mária Lakatos
wiley +1 more source
An Econometric Study of Vine Copulas [PDF]
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.
Dominique Guegan, Pierre-André Maugis
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COBASE: A new copula‐based shuffling method for ensemble weather forecast postprocessing
Quarterly Journal of the Royal Meteorological Society, EarlyView.We propose COBASE, a novel copula‐based postprocessing methododology that combines the strengths of multivariate parametric correction with non‐parametric rank‐based approaches. We consider two case studies for multi‐site temperature in Austria and multi‐site temperature and dew‐point temperature in the Netherlands.
Maurits Flos +4 more
wiley +1 more source
Nonparametric Estimation of Copulas for Time Series [PDF]
We consider a nonparametric method to estimate copulas, i.e. functions linking joint distributions to their univariate margins. We derive the asymptotic properties of kernel estimators of copulas and their derivatives in the context of a multivariate ...
Jean-David FERMANIAN, Olivier SCAILLET
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River, EarlyView.Study of meteorological‐hydrological drought propagation under reservoir regulation using a Copula‐Bayesian network in the Hanjiang River Basin. Abstract Reservoir operations play a pivotal role in modifying drought propagation processes, particularly by influencing the transition from meteorological to hydrological drought. This study investigates the
Yanping Qu +5 more
wiley +1 more source
Tails of correlation mixtures of elliptical copulas
, 2009 Correlation mixtures of elliptical copulas arise when the correlation parameter is driven itself by a latent random process. For such copulas, both penultimate and asymptotic tail dependence are much larger than for ordinary elliptical copulas with the ...
Manner, Hans, Segers, Johan
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