Positive definite norm dependent matrices in stochastic modeling

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Abstract

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. © Copyright by Faculty of Mathematics and Information Science, Warsaw University of Technology.

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APA

Kuniewski, S. P., & Misiewicz, J. K. (2014). Positive definite norm dependent matrices in stochastic modeling. Demonstratio Mathematica, 47(1), 211–231. https://doi.org/10.2478/dema-2014-0017

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