ISBN: 9780691036991

A cornerstone of applied probability, Markov chains can be used to help model how plants grow, chemicals react, and atoms diffuse--and applications are increasingly being found in such areas as engineering, computer science, economics, and education. To apply the techniques to real problems, however, it is necessary to understand how Markov chains can be solved numerically. In this book, the first to offer a systematic and detailed treatment of the numerical solution of Markov chains, William Stewart provides scientists on many levels with the power to put this theory to use in the actual world, where it has applications in areas as diverse as engineering, economics, and education. His efforts make for essential reading in a rapidly growing field. Here Stewart explores all aspects of numerically computing solutions of Markov chains, especially when the state is huge. He provides extensive background to both discrete-time and continuous-time Markov chains and examines many different numerical computing methods--direct, single-and multi-vector iterative, and projection methods. More specifically, he considers recursive methods often used when the structure of the Markov chain is upper Hessenberg, iterative aggregation/disaggregation methods that are particularly appropriate when it is NCD (nearly completely decomposable), and reduced schemes for cases in which the chain is periodic. There are chapters on methods for computing transient solutions, on stochastic automata networks, and, finally, on currently available software. Throughout Stewart draws on numerous examples and comparisons among the methods he so thoroughly explains. William J. Stewart, Books, Introduction to the Numerical Solution of Markov Chains Books, Princeton University Press

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ISBN: 9780691036991

A cornerstone of applied probability, Markov chains can be used to help model how plants grow, chemicals react, and atoms diffuse--and applications are increasingly being found in such areas as engineering, computer science, economics, and education. To apply the techniques to real problems, however, it is necessary to understand how Markov chains can be solved numerically. In this book, the first to offer a systematic and detailed treatment of the numerical solution of Markov chains, William Stewart provides scientists on many levels with the power to put this theory to use in the actual world, where it has applications in areas as diverse as engineering, economics, and education. His efforts make for essential reading in a rapidly growing field. Here Stewart explores all aspects of numerically computing solutions of Markov chains, especially when the state is huge. He provides extensive background to both discrete-time and continuous-time Markov chains and examines many different numerical computing methods--direct, single-and multi-vector iterative, and projection methods. More specifically, he considers recursive methods often used when the structure of the Markov chain is upper Hessenberg, iterative aggregation/disaggregation methods that are particularly appropriate when it is NCD (nearly completely decomposable), and reduced schemes for cases in which the chain is periodic. There are chapters on methods for computing transient solutions, on stochastic automata networks, and, finally, on currently available software. Throughout Stewart draws on numerous examples and comparisons among the methods he so thoroughly explains. Introduction to the Numerical Solution of Markov Chains Stewart, William J. / Stewart, James, Princeton University Press

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ISBN: 9780691036991

A cornerstone of applied probability, Markov chains can be used to help model how plants grow, chemicals react, and atoms diffuse--and applications are increasingly being found in such areas as engineering, computer science, economics, and education. To apply the techniques to real problems, however, it is necessary to understand how Markov chains can be solved numerically. In this book, the first to offer a systematic and detailed treatment of the numerical solution of Markov chains, William Stewart provides scientists on many levels with the power to put this theory to use in the actual world, where it has applications in areas as diverse as engineering, economics, and education. His efforts make for essential reading in a rapidly growing field. Here Stewart explores all aspects of numerically computing solutions of Markov chains, especially when the state is huge. He provides extensive background to both discrete-time and continuous-time Markov chains and examines many different numerical computing methods--direct, single-and multi-vector iterative, and projection methods. More specifically, he considers recursive methods often used when the structure of the Markov chain is upper Hessenberg, iterative aggregation/disaggregation methods that are particularly appropriate when it is NCD (nearly completely decomposable), and reduced schemes for cases in which the chain is periodic. There are chapters on methods for computing transient solutions, on stochastic automata networks, and, finally, on currently available software. Throughout Stewart draws on numerous examples and comparisons among the methods he so thoroughly explains. Books List_Books, [PU: Princeton University Press]

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ISBN: 0691036993

A cornerstone of applied probability, Markov chains can be used to help model how plants grow, chemicals react, and atoms diffuse--and applications are increasingly being found in such areas as engineering, computer science, economics, and education. To apply the techniques to real problems, however, it is necessary to understand how Markov chains can be solved numerically. In this book, the first to offer a systematic and detailed treatment of the numerical solution of Markov chains, William Stewart provides scientists on many levels with the power to put this theory to use in the actual world, where it has applications in areas as diverse as engineering, economics, and education. His efforts make for essential reading in a rapidly growing field. Here Stewart explores all aspects of numerically computing solutions of Markov chains, especially when the state is huge. He provides extensive background to both discrete-time and continuous-time Markov chains and examines many different numerical computing methods--direct, single-and multi-vector iterative, and projection methods. More specifically, he considers recursive methods often used when the structure of the Markov chain is upper Hessenberg, iterative aggregation/disaggregation methods that are particularly appropriate when it is NCD (nearly completely decomposable), and reduced schemes for cases in which the chain is periodic. There are chapters on methods for computing transient solutions, on stochastic automata networks math,mathematics,science and math,science and math,statistics,textbooks Statistics, Princeton University Press

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ISBN: 9780691036991

Erscheinungsdatum: 04.12.1994, Medium: Buch, Einband: Gebunden, Titel: Introduction to the Numerical Solution of Markov Chains, Autor: Stewart, William J., Verlag: Princeton University Press, Sprache: Englisch, Schlagworte: MATHEMATICS // Probability & Statistics // Stochastic Processes, Rubrik: Mathematik // Wahrscheinlichkeitstheorie, Seiten: 562, Informationen: 68:B&W 7 x 10 in or 254 x 178 mm Case Laminate on White w/Gloss Lam, Gewicht: 1186 gr, Verkäufer: averdo Belletristik, [PU: Princeton University Press]

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ISBN: 9780691036991

A cornerstone of applied probability, Markov chains can be used to help model how plants grow, chemicals react, and atoms diffuse--and applications are increasingly being found in such ar… More...

## Stewart, William J. / Stewart, James:

Introduction to the Numerical Solution of Markov Chains*- used book*

ISBN: 9780691036991

A cornerstone of applied probability, Markov chains can be used to help model how plants grow, chemicals react, and atoms diffuse--and applications are increasingly being found in such ar… More...

## ISBN: 9780691036991

A cornerstone of applied probability, Markov chains can be used to help model how plants grow, chemicals react, and atoms diffuse--and applications are increasingly being found in such ar… More...

ISBN: 0691036993

ISBN: 9780691036991

Erscheinungsdatum: 04.12.1994, Medium: Buch, Einband: Gebunden, Titel: Introduction to the Numerical Solution of Markov Chains, Autor: Stewart, William J., Verlag: Princeton University Pr… More...

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** Details of the book - Introduction to the Numerical Solution of Markov Chains**

EAN (ISBN-13): 9780691036991

ISBN (ISBN-10): 0691036993

Hardcover

Paperback

Publishing year: 1994

Publisher: PRINCETON UNIV PR

539 Pages

Weight: 1,284 kg

Language: eng/Englisch

Book in our database since 2007-07-06T23:25:52+01:00 (London)

Detail page last modified on 2021-01-02T20:46:17+00:00 (London)

ISBN/EAN: 0691036993

ISBN - alternate spelling:

0-691-03699-3, 978-0-691-03699-1

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