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Characterization of pre-idempotent Copulas [PDF]
Dependence Modeling, 2023 Copulas CC for which (CtC)2=CtC{({C}^{t}C)}^{2}={C}^{t}C are called pre-idempotent copulas, of which well-studied examples are idempotent copulas and complete dependence copulas.
Chamnan Wongtawan, Sumetkijakan Songkiat
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Uniform distribution theory, 2023 Two-dimensional distribution function g(x, y) defined in [0, 1]2 is called copula, if g(x, 1) = x and g(1,y)= y for every x, y. Similarly, s-dimensional copula is a distribution function g(x1,x2,...,xs) such that every k-dimensional face function g(1,…,1,
O. Strauch, V. Baláž
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Statistica, 2018 Copulas are used to specify dependence between two or more random variables. The last few years have seen a surge of developments of parametric models for copulas.
Saralees Nadarajah +2 more
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Why Are FGM Copulas Successful? A Simple Explanation
Advances in Fuzzy Systems, 2018 One of the most computationally convenient nonredundant ways to describe the dependence between two variables is by describing the corresponding copula.
Songsak Sriboonchitta, Vladik Kreinovich
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Copula-based risk aggregation with trapped ion quantum computers. [PDF]
Sci Rep, 2023 Zhu D +5 more
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Revisiting Gaussian copulas to handle endogenous regressors
Journal of the Academy of Marketing Science, 2021 Marketing researchers are increasingly taking advantage of the instrumental variable (IV)-free Gaussian copula approach. They use this method to identify and correct endogeneity when estimating regression models with non-experimental data.
Jan-Michael Becker +2 more
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Copulas for hydroclimatic analysis: A practice‐oriented overview
WIREs Water, 2022 A warming climate is associated with increasing hydroclimatic extremes, which are often interconnected through complex processes, prompting their concurrence and/or succession, and causing compound extreme events.
Faranak Tootoonchi +5 more
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Novel Construction of Copulas Based on (α,β) Transformation for Fuzzy Random Variables
Journal of Mathematics, 2021 The paper introduces a method for the construction of bivariate copulas with the usage of specific values of the parameters α and β (α,β transformation) and the parameters κ and λ in their domain.
Stylianos Giakoumakis +1 more
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covsim: An R Package for Simulating Non-Normal Data for Structural Equation Models Using Copulas
Journal of Statistical Software, 2022 In factor analysis and structural equation modeling non-normal data simulation is traditionally performed by specifying univariate skewness and kurtosis together with the target covariance matrix.
Steffen Grønneberg +2 more
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Matrix-Tilted Archimedean Copulas
Risks, 2021 The new class of matrix-tilted Archimedean copulas is introduced. It combines properties of Archimedean and elliptical copulas by introducing a tilting matrix in the stochastic representation of Archimedean copulas, similar to the Cholesky factor for ...
Marius Hofert, Johanna F. Ziegel
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