Positive Definite Norm Dependent Matrices In Stochastic Modeling release_rtlbzbtkvzgt3b6eedl6py6xbu

by Sebastian P. Kuniewski, Jolanta K. Misiewicz

Published in Demonstratio Mathematica by Walter de Gruyter GmbH.

2014   Volume 47

Abstract

<jats:title>Abstract</jats:title>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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