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- catalog abstract ""This book provides a self-contained and up-to-date treatment of the Monte Carlo method and develops a common framework under which various Monte Carlo techniques can be "standardized" and compared. Given the interdisciplinary nature of the topics and a moderate prerequisite for the reader, this book should be of interest to a broad audience of quantitative researchers such as computational biologists, computer scientists, econometricians, engineers, probabilists, and statisticians. It can also be used as the textbook for a graduate-level course on Monte Carlo methods. Many problems discussed in the later chapters can be potential thesis topics for master's or Ph. D. students in statistics or computer science departments."--Jacket.".
- catalog contributor b12552799.
- catalog created "c2001.".
- catalog date "2001".
- catalog date "c2001.".
- catalog dateCopyrighted "c2001.".
- catalog description ""This book provides a self-contained and up-to-date treatment of the Monte Carlo method and develops a common framework under which various Monte Carlo techniques can be "standardized" and compared. Given the interdisciplinary nature of the topics and a moderate prerequisite for the reader, this book should be of interest to a broad audience of quantitative researchers such as computational biologists, computer scientists, econometricians, engineers, probabilists, and statisticians. It can also be used as the textbook for a graduate-level course on Monte Carlo methods. Many problems discussed in the later chapters can be potential thesis topics for master's or Ph. D. students in statistics or computer science departments."--Jacket.".
- catalog description "Includes bibliographical references (p. [313]-332) and indexes.".
- catalog description "Preface -- 1. Introduction and examples -- 2. Basic principles : rejection, weighting, and others -- 3. Theory of sequential Monte Carlo -- 4. Sequential Monte Carlo in action -- 5. Metropolis algorithm and beyond -- 6. The Gibbs sampler -- 7. Cluster algorithms for the Ising model -- 8. General conditional sampling -- 9. Molecular dynamics and hybrid Monte Carlo -- 10. Multilevel sampling and optimization methods -- 11. Population-based Monte Carlo methods -- 12. Markov chains and their convergence -- 13. Selected theoretical topics -- A. Basics in probability and statistics -- References -- Author index -- Subject index.".
- catalog extent "xvi, 343 p. :".
- catalog identifier "0387952306 (alk. paper)".
- catalog isPartOf "Springer series in statistics".
- catalog issued "2001".
- catalog issued "c2001.".
- catalog language "eng".
- catalog publisher "New York : Springer,".
- catalog subject "501/.519282 21".
- catalog subject "Monte Carlo method.".
- catalog subject "Q180.55.S7 L58 2001".
- catalog subject "Science Statistical methods.".
- catalog tableOfContents "Preface -- 1. Introduction and examples -- 2. Basic principles : rejection, weighting, and others -- 3. Theory of sequential Monte Carlo -- 4. Sequential Monte Carlo in action -- 5. Metropolis algorithm and beyond -- 6. The Gibbs sampler -- 7. Cluster algorithms for the Ising model -- 8. General conditional sampling -- 9. Molecular dynamics and hybrid Monte Carlo -- 10. Multilevel sampling and optimization methods -- 11. Population-based Monte Carlo methods -- 12. Markov chains and their convergence -- 13. Selected theoretical topics -- A. Basics in probability and statistics -- References -- Author index -- Subject index.".
- catalog title "Monte Carlo strategies in scientific computing / Jun S. Liu.".
- catalog type "text".