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Table of contents (8 chapters)
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Front Matter
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Back Matter
Keywords
- network analysis
- network structure identification
- robust statistical procedures
- statistical procedures for network structure identification
- Risk functions for network structure identification
- stock market networks
- graphical model selections
- random variable networks
- maximum spanning trees
- maximum clique
About this book
This book studies complex systems with elements represented by random variables. Its main goal is to study and compare uncertainty of algorithms of network structure identification with applications to market network analysis. For this, a mathematical model of random variable network is introduced, uncertainty of identification procedure is defined through a risk function, random variables networks with different measures of similarity (dependence) are discussed, and general statistical properties of identification algorithms are studied. The volume also introduces a new class of identification algorithms based on a new measure of similarity and prove its robustness in a large class of distributions, and presents applications to social networks, power transmission grids, telecommunication networks, stock market networks, and brain networks through a theoretical analysis that identifies network structures. Both researchers and graduate students in computer science, mathematics, and optimization will find the applications and techniques presented useful.
Authors and Affiliations
Bibliographic Information
Book Title: Statistical Analysis of Graph Structures in Random Variable Networks
Authors: V. A. Kalyagin, A. P. Koldanov, P. A. Koldanov, P. M. Pardalos
Series Title: SpringerBriefs in Optimization
DOI: https://doi.org/10.1007/978-3-030-60293-2
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: The Author(s) 2020
Softcover ISBN: 978-3-030-60292-5Published: 06 December 2020
eBook ISBN: 978-3-030-60293-2Published: 05 December 2020
Series ISSN: 2190-8354
Series E-ISSN: 2191-575X
Edition Number: 1
Number of Pages: VIII, 101
Number of Illustrations: 6 b/w illustrations, 3 illustrations in colour
Topics: Optimization, Computer Systems Organization and Communication Networks, Probability Theory and Stochastic Processes, Mathematical Models of Cognitive Processes and Neural Networks