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Trivariate Stochastic Weather Model for Predicting Maize Yield
Journal of Applied Mathematics, Volume 2022, Issue 1, 2022., 2022 Maize yield prediction in the sub‐Saharan region is imperative for mitigation of risks emanating from crop loss due to changes in climate. Temperature, rainfall amount, and reference evapotranspiration are major climatic factors affecting maize yield.
Patrick Chidzalo +3 more
wiley +1 more source
Study on drought events in China based on time-varying nested Archimedean-copula function
Water Supply, 2021 Abstract Drought forecasting, which can enable contingency actions to be implemented in advance of a drought, plays a significant role in reducing the risks and impacts of drought. In this study, a simulation framework of the occurrence probability of drought events based on a nested copula function and Gibbs sampling is proposed to ...
Ziyang Zhao +3 more
openaire +2 more sources
Construction and sampling of Archimedean and nested Archimedean Lévy copulas
Journal of Multivariate Analysis, 2015 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Oliver Grothe, Marius Hofert
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Capturing non-exchangeable dependence in multivariate loss processes with nested Archimedean Lévy copulas [PDF]
Annals of Actuarial Science, 2014 AbstractThe class of spectrally positive Lévy processes is a frequent choice for modelling loss processes in areas such as insurance or operational risk. Dependence between such processes (e.g. between different lines of business) can be modelled with Lévy copulas.
Avanzi, B, Tao, J, Wong, B, Yang, X
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Journal of Mathematics, Volume 2021, Issue 1, 2021., 2021 This paper investigates the risk contribution of 29 industrial sectors to the China stock market by using one‐factor with Durante generator copulas (FDG) and component expected shortfall (CES) analyses. Risk contagion between the systemically most important sector and other sectors is examined using a copula‐based ∆CoVaR approach.
Jianxu Liu +6 more
wiley +1 more source
Water Resources Management, 2022 Abstract Severe flooding in coastal areas can result from the joint probability of multiple extreme or non-extreme oceanographic, hydrological, and meteorological factors, resulting in compound flooding (CF) events if they occur successively or simultaneously.
Shahid Latif, Slobodan P. Simonovic
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On the estimation of nested Archimedean copulas: a theoretical and an experimental comparison [PDF]
Computational Statistics, 2017 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Environmental Earth Sciences, 2022 Abstract Compound flooding is a multidimensional consequence of the joint impact of multiple intercorrelated drivers such as oceanographic, hydrologic, and meteorological. These individual drivers exhibit interdependence due to common forcing mechanisms.
Shahid Latif, Slobodan P. Simonovic
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Copulas, stable tail dependence functions, and multivariate monotonicity
Dependence Modeling, 2019 For functions of several variables there exist many notions of monotonicity, three of them being characteristic for resp. distribution, survival and co-survival functions. In each case the “degree” of monotonicity is just the basic one of a whole scale.
Ressel Paul
doaj +1 more source
Pair-copula constructions of multiple dependence [PDF]
, 2006 Building on the work of Bedford, Cooke and Joe, we show how multivariate data, which exhibit complex patterns of dependence in the tails, can be modelled using a cascade of pair-copulae, acting on two variables at a time.
Aas, Kjersti +3 more
core +1 more source