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Perfect simulation /
Exact sampling, specifically coupling from the past (CFTP), allows users to sample exactly from the stationary distribution of a Markov chain. During its nearly 20 years of existence, exact sampling has evolved into perfect simulation, which enables high-dimensional simulation from interacting distr...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Boca Raton, FL :
CRC Press, Taylor & Francis Group,
[2016]
|
| Colección: | Monographs on statistics and applied probability (Series) ;
148. |
| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
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| 100 | 1 | |a Huber, Mark Lawrence, |d 1972- |e author. | |
| 245 | 1 | 0 | |a Perfect simulation / |c Mark L. Huber. |
| 264 | 1 | |a Boca Raton, FL : |b CRC Press, Taylor & Francis Group, |c [2016] | |
| 300 | |a 1 online resource (xxii, 228 pages) : |b illustrations | ||
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| 490 | 1 | |a Monographs on statistics and applied probability ; |v 148 | |
| 504 | |a Includes bibliographical references (pages 219-226) and index. | ||
| 588 | 0 | |a Print version record. | |
| 505 | 0 | |a Front Cover; Contents; List of Figures; List of Tables; Preface; Chapter 1: Introduction; Chapter 2: Acceptance/Rejection; Chapter 3: Coupling from the Past; Chapter 4: Bounding Chains; Chapter 5: Advanced Techniques Using Coalescence; Chapter 6: Coalescence on Continuous and Unbounded State Spaces; Chapter 7: Spatial Point Processes; Chapter 8: The Randomness Recycler; Chapter 9: Advanced Acceptance/Rejection; Chapter 10: Stochastic Differential Equations; Chapter 11: Applications and Limitations of Perfect Simulation; Bibliography; Back Cover. | |
| 520 | 8 | |a Exact sampling, specifically coupling from the past (CFTP), allows users to sample exactly from the stationary distribution of a Markov chain. During its nearly 20 years of existence, exact sampling has evolved into perfect simulation, which enables high-dimensional simulation from interacting distributions. Perfect Simulation illustrates the application of perfect simulation ideas and algorithms to a wide range of problems. The book is one of the first to bring together research on simulation from statistics, physics, finance, computer science, and other areas into a unified framework. You will discover the mechanisms behind creating perfect simulation algorithms for solving an array of problems. The author describes numerous protocol methodologies for designing algorithms for specific problems. He first examines the commonly used acceptance/rejection (AR) protocol for creating perfect simulation algorithms. He then covers other major protocols, including CFTP; the Fill, Machida, Murdoch, and Rosenthal (FMMR) method; the randomness recycler; retrospective sampling; and partially recursive AR, along with multiple variants of these protocols. The book also shows how perfect simulation methods have been successfully applied to a variety of problems, such as Markov random fields, permutations, stochastic differential equations, spatial point processes, Bayesian posteriors, combinatorial objects, and Markov processes. | |
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| 650 | 0 | |a Perfect simulation (Statistics) | |
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| 650 | 7 | |a MATHEMATICS |x Probability & Statistics |x General. |2 bisacsh | |
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| 776 | 0 | 8 | |i Print version: |a Huber, Mark Lawrence, 1972- |t Perfect simulation |z 9781482232448 |w (DLC) 2015027117 |w (OCoLC)925783475 |
| 830 | 0 | |a Monographs on statistics and applied probability (Series) ; |v 148. | |
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