Results 1 to 10 of about 56 (56)
Stochastic orders of log-epsilon-skew-normal distributions
Analele Stiintifice ale Universitatii Ovidius Constanta: Seria Matematica, 2022 The log-epsilon-skew-normal distributions family is generalized class of log-normal distribution. Is widely used to model non-negative data in many areas of applied research.
Catana Luigi-Ionut
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Veterinary Dermatology, Volume 34, Issue 6, Page 543-553, December 2023., 2023 Background – Hymenoptera envenomation with honey bee (Apis mellifera) and paper wasp (Polistes spp.) may cause life‐threatening anaphylaxis in dogs. In human patients, clinical history, intradermal testing (IDT) and measurement of allergen‐specific serological immunoglobulin (Ig)E (sIgE) are used to support a diagnosis of Hymenoptera venom ...
Hilary H. Chan +3 more
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Strengthened inequalities for the mean width and the ℓ‐norm
Journal of the London Mathematical Society, Volume 104, Issue 1, Page 233-268, July 2021., 2021 Abstract Barthe proved that the regular simplex maximizes the mean width of convex bodies whose John ellipsoid (maximal volume ellipsoid contained in the body) is the Euclidean unit ball; or equivalently, the regular simplex maximizes the ℓ‐norm of convex bodies whose Löwner ellipsoid (minimal volume ellipsoid containing the body) is the Euclidean unit
Károly J. Böröczky +2 more
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Stochastic orders for a multivariate Pareto distribution
Analele Stiintifice ale Universitatii Ovidius Constanta: Seria Matematica, 2021 In this article we give some theoretical results for equivalence between different stochastic orders of some kind multivariate Pareto distribution family.
Catana Luigi-Ionut
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From Hardy to Rellich inequalities on graphs
Proceedings of the London Mathematical Society, Volume 122, Issue 3, Page 458-477, March 2021., 2021 Abstract We show how to deduce Rellich inequalities from Hardy inequalities on infinite graphs. Specifically, the obtained Rellich inequality gives an upper bound on a function by the Laplacian of the function in terms of weighted norms. These weights involve the Hardy weight and a function which satisfies an eikonal inequality.
Matthias Keller +2 more
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A combinatorial proof of the Gaussian product inequality beyond the MTP2 case
Dependence Modeling, 2022 A combinatorial proof of the Gaussian product inequality (GPI) is given under the assumption that each component of a centered Gaussian random vector X=(X1,…,Xd){\boldsymbol{X}}=\left({X}_{1},\ldots ,{X}_{d}) of arbitrary length can be written as a ...
Genest Christian, Ouimet Frédéric
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A note on stochastic dominance, uniform integrability and lattice properties
Bulletin of the London Mathematical Society, Volume 52, Issue 5, Page 907-923, October 2020., 2020 Abstract In this work, we discuss completeness for the lattice orders of first and second order stochastic dominance. The main results state that both first‐ and second‐order stochastic dominance induce Dedekind super complete lattices, that is, lattices in which every bounded nonempty subset has a countable subset with identical least upper bound and ...
Max Nendel
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Antisymmetry of the Stochastical Order on all Ordered Topological Spaces
Analysis and Geometry in Metric Spaces, 2019 In this short note, we prove that the stochastic order of Radon probability measures on any ordered topological space is antisymmetric. This has been known before in various special cases. We give a simple and elementary proof of the general result.
Fritz Tobias
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Bounds for distribution functions of sums of squares and radial errors
International Journal of Mathematics and Mathematical Sciences, Volume 14, Issue 3, Page 561-569, 1991., 1991 Bounds are found for the distribution function of the sum of squares X2 + Y2 where X and Y are arbitrary continuous random variables. The techniques employed, which utilize copulas and their properties, show that the bounds are pointwise best‐possible when X and Y are symmetric about 0 and yield expressions which can be evaluated explicitly when X and ...
Roger B. Nelsen, Berthold Schweizer
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VaR bounds in models with partial dependence information on subgroups
Dependence Modeling, 2017 We derive improved estimates for the model risk of risk portfolios when additional to the marginals some partial dependence information is available.We consider models which are split into k subgroups and consider various classes of dependence ...
Rüschendorf Ludger, Witting Julian
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