The Experts below are selected from a list of 318 Experts worldwide ranked by ideXlab platform
Marco Scarsini - One of the best experts on this subject based on the ideXlab platform.
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Zonoids, Linear Dependence, and size-biased distributions on the simplex
Advances in Applied Probability, 2020Co-Authors: Marco Dall'aglio, Marco ScarsiniAbstract:The zonoid of a d-dimensional random vector is used as a tool for measuring Linear Dependence among its components. A preorder of Linear Dependence is defined through inclusion of the zonoids. The zonoid of a random vector does not characterize its distribution, but it does characterize the size-biased distribution of its compositional variables. This fact will allow a characterization of our Linear Dependence order in terms of a Linear-convex order for the size-biased compositional variables. In dimension 2 the Linear Dependence preorder will be shown to be weaker than the concordance order. Some examples related to the Marshall-Olkin distribution and to a copula model will be presented, and a class of measures of Linear Dependence will be proposed.
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Zonoids, Linear Dependence, and Size-Biased Distributions on the Simplex
2003Co-Authors: Marco Dall'aglio, Marco ScarsiniAbstract:The zonoid of a d-dimensional random vector is used as a tool for measuring Linear Dependence among its components. A preorder of Linear Dependence is defined through inclusion of the zonoids. The zonoid of a random vector does not characterize its distribution, but it characterizes the size biased distribution of its compositional variables. This fact will allow a characterization of our Linear Dependence order in terms of a Linear-convex order for the size-biased compositional variables. In dimension 2 the Linear Dependence preorder will be shown to be weaker than the concordance order. Some examples related to the Marshall-Olkin distribution and to a copula model will be presented, and a class of measures of Linear Dependence will be proposed.
Marco Dall'aglio - One of the best experts on this subject based on the ideXlab platform.
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Zonoids, Linear Dependence, and size-biased distributions on the simplex
Advances in Applied Probability, 2020Co-Authors: Marco Dall'aglio, Marco ScarsiniAbstract:The zonoid of a d-dimensional random vector is used as a tool for measuring Linear Dependence among its components. A preorder of Linear Dependence is defined through inclusion of the zonoids. The zonoid of a random vector does not characterize its distribution, but it does characterize the size-biased distribution of its compositional variables. This fact will allow a characterization of our Linear Dependence order in terms of a Linear-convex order for the size-biased compositional variables. In dimension 2 the Linear Dependence preorder will be shown to be weaker than the concordance order. Some examples related to the Marshall-Olkin distribution and to a copula model will be presented, and a class of measures of Linear Dependence will be proposed.
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Zonoids, Linear Dependence, and Size-Biased Distributions on the Simplex
2003Co-Authors: Marco Dall'aglio, Marco ScarsiniAbstract:The zonoid of a d-dimensional random vector is used as a tool for measuring Linear Dependence among its components. A preorder of Linear Dependence is defined through inclusion of the zonoids. The zonoid of a random vector does not characterize its distribution, but it characterizes the size biased distribution of its compositional variables. This fact will allow a characterization of our Linear Dependence order in terms of a Linear-convex order for the size-biased compositional variables. In dimension 2 the Linear Dependence preorder will be shown to be weaker than the concordance order. Some examples related to the Marshall-Olkin distribution and to a copula model will be presented, and a class of measures of Linear Dependence will be proposed.
Haruo Terasaka - One of the best experts on this subject based on the ideXlab platform.
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Linear Dependence problems of partition of unity based generalized fems
Computer Methods in Applied Mechanics and Engineering, 2006Co-Authors: Rong Tian, Genki Yagawa, Haruo TerasakaAbstract:A known problem of partition of unity-based generalized finite element methods (referred to as GFEM) is the Linear Dependence problem, which leads to singular global (stiffness) matrices. Thus far attempts to eliminate the Linear Dependence problem have been unsuccessful. Numerical experiments are carried out among several GFEMs to investigate the problem. Based on the numerical experiments, simple but effective approaches to eliminating the Linear Dependence problem are suggested.
Xiaoying Zhuang - One of the best experts on this subject based on the ideXlab platform.
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a new partition of unity finite element free from the Linear Dependence problem and possessing the delta property
Computer Methods in Applied Mechanics and Engineering, 2010Co-Authors: Xiaoying Zhuang, C E AugardeAbstract:Partition of unity based finite element methods (PUFEMs) have appealing capabilities for p-adaptivity and local refinement with minimal or even no remeshing of the problem domain. However, PUFEMs suffer from a number of problems that practically limit their application, namely the Linear Dependence (LD) problem, which leads to a singular global stiffness matrix, and the difficulty with which essential boundary conditions can be imposed due to the lack of the Kronecker delta property. In this paper we develop a new PU-based triangular element using a dual local approximation scheme by treating boundary and interior nodes separately. The present method is free from the LD problem and essential boundary conditions can be applied directly as in the FEM. The formulation uses triangular elements, however the essential idea is readily extendable to other types of meshed or meshless formulation based on a PU approximation. The computational cost of the present method is comparable to other PUFEM elements described in the literature. The proposed method can be simply understood as a PUFEM with composite shape functions possessing the delta property and appropriate compatibility.
Juan C Fernandez - One of the best experts on this subject based on the ideXlab platform.
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Linear Dependence of surface expansion speed on initial plasma temperature in warm dense matter
Scientific Reports, 2016Co-Authors: W Bang, B J Albright, P A Bradley, E L Vold, J C Boettger, Juan C FernandezAbstract:Recent progress in laser-driven quasi-monoenergetic ion beams enabled the production of uniformly heated warm dense matter. Matter heated rapidly with this technique is under extreme temperatures and pressures, and promptly expands outward. While the expansion speed of an ideal plasma is known to have a square-root Dependence on temperature, computer simulations presented here show a Linear Dependence of expansion speed on initial plasma temperature in the warm dense matter regime. The expansion of uniformly heated 1–100 eV solid density gold foils was modeled with the RAGE radiation-hydrodynamics code, and the average surface expansion speed was found to increase Linearly with temperature. The origin of this Linear Dependence is explained by comparing predictions from the SESAME equation-of-state tables with those from the ideal gas equation-of-state. These simulations offer useful insight into the expansion of warm dense matter and motivate the application of optical shadowgraphy for temperature measurement.
