Authors:
- Markov chains are a powerful and widely used tool for analyzing a variety of stochastic systems over time
- Systematically discusses all the models beginning with the basic to the more advanced and illustrates each of the models with the most recent and high interest applications and uses
- Includes supplementary material: sn.pub/extras
Part of the book series: International Series in Operations Research & Management Science (ISOR, volume 83)
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Table of contents (8 chapters)
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Front Matter
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Back Matter
About this book
Markov chains are a particularly powerful and widely used tool for analyzing a variety of stochastic (probabilistic) systems over time. This monograph will present a series of Markov models, starting from the basic models and then building up to higher-order models. Included in the higher-order discussions are multivariate models, higher-order multivariate models, and higher-order hidden models. In each case, the focus is on the important kinds of applications that can be made with the class of models being considered in the current chapter. Special attention is given to numerical algorithms that can efficiently solve the models.
Therefore, Markov Chains: Models, Algorithms and Applications outlines recent developments of Markov chain models for modeling queueing sequences, Internet, re-manufacturing systems, reverse logistics, inventory systems, bio-informatics, DNA sequences, genetic networks, data mining, and many other practical systems.
Reviews
From the reviews:
"The authors outline recent developments of Markov chain models … . This book is aimed at students, professionals, practitioners, and researchers in scientific computing and operational research, who are interested in the formulation and computation of queuing and manufacturing systems. It gives a number of useful tools for researchers in real applications … ." (Alexander I. Zejfman, Zentralblatt MATH, Vol. 1089 (15), 2006)
"In this book’s … essential notions on Markov chains, hidden Markov models, and Markov decision processes are covered, with special emphasis on iterative methods for solving linear systems. … Each chapter finishes with a short summary and sometimes a selection of open problems. … This book is intended for students and researchers in applied mathematics, scientific computing, and operations research … . Overall, this book offers much interesting and up-to-date material on a wide variety of topics, dealing with finite-space Markov processes." (Jozef L. Teugels, Journal of the American Statistical Association, Vol. 103 (483), September, 2008)
Authors and Affiliations
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The University of Hong Kong, Hong Kong, P.R. China
Wai-Ki Ching
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Hong Kong Baptist University, Hong Kong, P.R. China
Michael K. Ng
Bibliographic Information
Book Title: Markov Chains: Models, Algorithms and Applications
Authors: Wai-Ki Ching, Michael K. Ng
Series Title: International Series in Operations Research & Management Science
DOI: https://doi.org/10.1007/0-387-29337-X
Publisher: Springer New York, NY
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer-Verlag US 2006
Softcover ISBN: 978-1-4419-3986-9Published: 25 November 2010
eBook ISBN: 978-0-387-29337-0Published: 05 June 2006
Series ISSN: 0884-8289
Series E-ISSN: 2214-7934
Edition Number: 1
Number of Pages: XIV, 208
Number of Illustrations: 18 b/w illustrations
Topics: Probability Theory and Stochastic Processes, Operations Research/Decision Theory, Mathematical Modeling and Industrial Mathematics, Operations Management, Probability and Statistics in Computer Science, Math Applications in Computer Science