Results 21 to 30 of about 157 (131)
Dependence Modeling, 2020 The use of the exponential distribution and its multivariate generalizations is extremely popular in lifetime modeling. Freund’s bivariate exponential model (1961) is based on the idea that the remaining lifetime of any entity in a bivariate system is ...
Guzmics Sándor, Pflug Georg Ch.
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About the exact simulation of bivariate (reciprocal) Archimax copulas
Dependence Modeling, 2022 We provide an exact simulation algorithm for bivariate Archimax copulas, including instances with negative association. In contrast to existing simulation approaches, the feasibility of our algorithm is directly linked to the availability of an exact ...
Mai Jan-Frederik
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Maximum asymmetry of copulas revisited
Dependence Modeling, 2018 Motivated by the nice characterization of copulas A for which d∞(A, At) is maximal as established independently by Nelsen [11] and Klement & Mesiar [7], we study maximum asymmetry with respect to the conditioning-based metric D1 going back to Trutschnig [
Kamnitui Noppadon +2 more
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Dependence Modeling, 2018 Williamson’s integral representation of n-monotone functions on the half-line is generalized to several dimensions. This leads to a characterization of multivariate survival functions with multiply ℓ1- symmetry.
Ressel Paul
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CMPH: a multivariate phase-type aggregate loss distribution
Dependence Modeling, 2017 We introduce a compound multivariate distribution designed for modeling insurance losses arising from different risk sources in insurance companies.
Ren Jiandong, Zitikis Ricardas
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Laplace transform of certain functions with applications
International Journal of Mathematics and Mathematical Sciences, Volume 23, Issue 2, Page 99-102, 2000., 2000 The Laplace transform of the functions tν(1+t)β, Reν > −1, is expressed in terms of Whittaker functions. This expression is exploited to evaluate infinite integrals involving products of Bessel functions, powers, exponentials, and Whittaker functions. Some special cases of the result are discussed. It is also demonstrated that the famous identity∫0∞sin
M. Aslam Chaudhry
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Modelling with star-shaped distributions
Dependence Modeling, 2020 We prove and describe in great detail a general method for constructing a wide range of multivariate probability density functions. We introduce probabilistic models for a large variety of clouds of multivariate data points.
Liebscher Eckhard, Richter Wolf-Dieter
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On convergence of associative copulas and related results
Dependence Modeling, 2021 Triggered by a recent article establishing the surprising result that within the class of bivariate Archimedean copulas 𝒞ar different notions of convergence - standard uniform convergence, convergence with respect to the metric D1, and so-called weak ...
Kasper Thimo M. +2 more
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A probablistic proof of the series representation of the MacDonald function with applications
International Journal of Mathematics and Mathematical Sciences, Volume 21, Issue 3, Page 463-466, 1998., 1993 A series representation of the Macdonald function is obtained using the properties of a probability density function and its moment generating function. Some applications of the result are discussed and an open problem is posed.
M. Aslam Chaudhry, Munir Ahmad
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New results on perturbation-based copulas
Dependence Modeling, 2021 A prominent example of a perturbation of the bivariate product copula (which characterizes stochastic independence) is the parametric family of Eyraud-Farlie-Gumbel-Morgenstern copulas which allows small dependencies to be modeled.
Saminger-Platz Susanne +4 more
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