Positive Definite Norm Dependent Matrices In Stochastic Modeling

Sebastian P. Kuniewski; Jolanta K. Misiewicz

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Positive Definite Norm Dependent Matrices In Stochastic Modeling

机译：Positive Definite Norm Dependent Matrices In Stochastic Modeling

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摘要

Positive definite norm dependent matrices are of interest in stochastic modeling of distance/norm dependent phenomena in nature. An example is the application of geostatistics in geographic information systems or mathematical analysis of varied spatial data. Because the positive definiteness is a necessary condition for a matrix to be a valid correlation matrix, it is desirable to give a characterization of the family of the distance/norm dependent functions that form a valid (positive definite) correlation matrix. Thus, the main reason for writing this paper is to give an overview of characterizations of norm dependent real functions and consequently norm dependent matrices, since this information is somehow hidden in the theory of geometry of Banach spaces.

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《Demonstratio Mathematica》 |2014年第1期|211-231|共21页
作者
Sebastian P. Kuniewski; Jolanta K. Misiewicz;
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作者单位

FACULTY OF ELECTRICAL ENGINEERING MATHEMATICS AND COMPUTER SCIENCE DELFT UNIVERSITY OF TECHNOLOGY THE NETHERLANDS;

DEPARTMENT OF MATHEMATICS AND INFORMATION SCIENCE WARSAW TECHNICAL UNIVERSITY WARSAW;

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正文语种英语
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correlation matrix; norm dependent function; positive definite function;

Positive Definite Norm Dependent Matrices In Stochastic Modeling

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