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Introduction to the numerical solution of Markov chains /
Markov Chains -- Direct Methods -- Iterative Methods -- Projection Methods -- Block Hessenberg Matrices -- Decompositional Methods -- LI-Cyclic Markov -- Chains -- Transient Solutions -- Stochastic Automata Networks -- Software.
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Princeton, N.J. :
Princeton University Press,
c1994.
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| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 100 | 1 | |a Stewart, William J., |d 1946- | |
| 245 | 1 | 0 | |a Introduction to the numerical solution of Markov chains / |c William J. Stewart. |
| 260 | |a Princeton, N.J. : |b Princeton University Press, |c c1994. | ||
| 300 | |a 1 online resource (xix, 539 p.) | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 504 | |a Includes bibliographical references (p. 513-527) and index. | ||
| 588 | |a Description based on print version record and CIP data provided by publisher; resource not viewed. | ||
| 505 | 0 | |a Markov chains -- Direct methods -- Iterative methods -- Projection methods -- Block Hessenberg matrices and solution by recursion -- Decompositional methods -- P-cyclic markov chains -- Transient solutions -- Stochastic automata networks -- Software. | |
| 520 | |a Markov Chains -- Direct Methods -- Iterative Methods -- Projection Methods -- Block Hessenberg Matrices -- Decompositional Methods -- LI-Cyclic Markov -- Chains -- Transient Solutions -- Stochastic Automata Networks -- Software. | ||
| 520 | |a 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. | ||
| 590 | |a JSTOR |b Books at JSTOR Evidence Based Acquisitions | ||
| 590 | |a JSTOR |b Books at JSTOR All Purchased | ||
| 590 | |a JSTOR |b Books at JSTOR Demand Driven Acquisitions (DDA) | ||
| 650 | 0 | |a Markov processes |x Numerical solutions. | |
| 650 | 6 | |a Processus de Markov |x Solutions numériques. | |
| 650 | 7 | |a MATHEMATICS |x Probability & Statistics |x Stochastic Processes. |2 bisacsh | |
| 650 | 7 | |a Markov processes |x Numerical solutions |2 fast | |
| 650 | 1 | 7 | |a Markov-processen. |2 gtt |
| 650 | 7 | |a Markov, Processus de. |2 ram | |
| 776 | 0 | 8 | |i Print version: |t Introduction to the numerical solution of Markov chains |d Princeton, N.J. : Princeton University Press, c1994. |z 0691036993 (acid-free paper) : |w (DLC) 94017465 |
| 856 | 4 | 0 | |u https://jstor.uam.elogim.com/stable/10.2307/j.ctv182jsw5 |z Texto completo |
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