Markov chain Monte Carlo : innovations and applications / edited by W.S. Kendall, F. Liang, J.-S. Wang.
Markov Chain Monte Carlo (MCMC) originated in statistical physics, but has spilled over into various application areas, leading to a corresponding variety of techniques and methods. That variety stimulates new ideas and developments from many different places, and there is much to be gained from cro...
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| Online Access: |
Full Text (via ProQuest) |
|---|---|
| Other Authors: | , , |
| Format: | eBook |
| Language: | English |
| Published: |
Singapore ; Hackensack, NJ :
World Scientific,
©2005.
|
| Series: | Lecture notes series (National University of Singapore. Institute for Mathematical Sciences) ;
v. 7. |
| Subjects: |
MARC
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| 245 | 0 | 0 | |a Markov chain Monte Carlo : |b innovations and applications / |c edited by W.S. Kendall, F. Liang, J.-S. Wang. |
| 260 | |a Singapore ; |a Hackensack, NJ : |b World Scientific, |c ©2005. | ||
| 300 | |a 1 online resource (xviii, 220 pages) : |b illustrations. | ||
| 336 | |a text |b txt |2 rdacontent. | ||
| 337 | |a computer |b c |2 rdamedia. | ||
| 338 | |a online resource |b cr |2 rdacarrier. | ||
| 490 | 1 | |a Lecture notes series, Institute for Mathematical Sciences, National University of Singapore ; |v vol. 7. | |
| 504 | |a Includes bibliographical references and index. | ||
| 505 | 0 | |a CONTENTS; Foreword; Preface; Glossary; Introduction to Markov Chain Monte Carlo Simulations and Their Statistical Analysis B.A. Berg; An Introduction to Monte Carlo Methods in Statistical Physics D.P. Landau; Notes on Perfect Simulation W.S. Kendall; Sequential Monte Carlo Methods and Their Applications R. Chen; MCMC in the Analysis of Genetic Data on Pedigrees E.A. Thompson; Index. | |
| 520 | |a Markov Chain Monte Carlo (MCMC) originated in statistical physics, but has spilled over into various application areas, leading to a corresponding variety of techniques and methods. That variety stimulates new ideas and developments from many different places, and there is much to be gained from cross-fertilization. This book presents five expository essays by leaders in the field, drawing from perspectives in physics, statistics and genetics, and showing how different aspects of MCMC come to the fore in different contexts. The essays derive from tutorial lectures at an interdisciplinary progr. | ||
| 650 | 0 | |a Monte Carlo method. | |
| 650 | 0 | |a Bayesian statistical decision theory. | |
| 650 | 0 | |a Markov processes. | |
| 650 | 7 | |a Bayesian statistical decision theory. |2 fast |0 (OCoLC)fst00829019. | |
| 650 | 7 | |a Markov processes. |2 fast |0 (OCoLC)fst01010347. | |
| 650 | 7 | |a Monte Carlo method. |2 fast |0 (OCoLC)fst01025819. | |
| 700 | 1 | |a Kendall, W. S. | |
| 700 | 1 | |a Liang, F. |q (Faming), |d 1970- | |
| 700 | 1 | |a Wang, J.-S. |q (Jian-Sheng), |d 1960- | |
| 776 | 0 | 8 | |i Print version: |t Markov chain Monte Carlo. |d Singapore ; Hackensack, NJ : World Scientific, ©2005 |w (DLC) 2006299138. |
| 830 | 0 | |a Lecture notes series (National University of Singapore. Institute for Mathematical Sciences) ; |v v. 7. | |
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