Results 91 to 100 of about 43,396 (279)
Convergence of Archimedean Copulas [PDF]
Convergence of a sequence of bivariate Archimedean copulas to another Archimedean copula or to the comonotone copula is shown to be equivalent with convergence of the corresponding sequence of Kendall distribution functions.No extra differentiability ...
Charpentier, A., Segers, J.J.J.
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Mathematical Methods in the Applied Sciences, EarlyView.We develop a full randomization of the classical hyper‐logistic growth model by obtaining closed‐form expressions for relevant quantities of interest, such as the first probability density function of its solution, the time until a given fixed population is reached, and the population at the inflection point.
Juan Carlos Cortés +2 more
wiley +1 more source
Improving Upon the Marginal Empirical Distribution Functions when the Copula is Known [PDF]
At the heart of the copula methodology in statistics is the idea of separating marginal distributions from the dependence structure. However, as shown in this paper, this separation is not to be taken for granted: in the model where the copula is known ...
Akker, R. van den +2 more
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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
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
Student copula method in rainfall distribution [PDF]
, 2015 Copulas are tools for modelling dependence of several random variables. The term copula was first used in the work of Sklar (1959) and is derived from the latin word copulare, to connect or to join.
Sahrin, Sharainie, Yusof, Fadhilah
core
Bivariate postprocessing of wind vectors
Quarterly Journal of the Royal Meteorological Society, EarlyView.We introduce three novel bivariate postprocessing approaches and analyze their performance for joint postprocessing of bivariate wind‐vector components in Germany. Bivariate vine‐copula‐based models, a bivariate gradient‐boosted version of ensemble model output statistics (EMOS), and a bivariate distributional regression network (DRN) are compared with
Ferdinand Buchner +3 more
wiley +1 more source
Research on the insurance of swimming crab temperature and salinity index insurance based on Copula function. [PDF]
PLoS One, 2022 Shi X +7 more
europepmc +1 more source
Statistical post‐processing of operational dual‐resolution wind‐speed ensemble forecasts
Quarterly Journal of the Royal Meteorological Society, EarlyView.The performance of raw and post‐processed 50‐member medium‐ and 100‐member extended‐range 10‐m wind‐speed forecasts of the European Centre for Medium‐Range Weather Forecasts and their various dual‐resolution combinations is investigated. Results show that post‐processing improves skill and reduces the differences between the various configurations ...
Sándor Baran, Mária Lakatos
wiley +1 more source
Testing the symmetry of a dependence structure with a characteristic function
Dependence Modeling, 2018 This paper proposes competing procedures to the tests of symmetry for bivariate copulas of Genest, Nešlehová and Quessy (2012). To this end, the null hypothesis of symmetry is expressed in terms of the copula characteristic function that uniquely ...
Bahraoui Tarik +2 more
doaj +1 more source