Introduction to the Numerical Solution of Markov Chains pdf epub mobi txt 电子书下载 2026

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出版者:Princeton University Press

作者:William J. Stewart

出品人:

页数:568

译者:

出版时间:1994-11-14

价格:USD 125.00

装帧:Hardcover

isbn号码:9780691036991

丛书系列:

图书标签:

Math
CS
2015
Markov Chains
Numerical Analysis
Stochastic Processes
Queueing Theory
Simulation
Probability
Algorithms
Computational Mathematics
Applied Probability
Monte Carlo Methods

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具体描述

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.

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