Monte Carlo strategies in scientific computing / Jun S. Liu.

Author
Liu, Jun S. [Browse]
Format
Book
Language
English
Published/​Created
New York : Springer, 2008.
Description
xvi, 343 pages : illustrations ; 24 cm.

Availability

Available Online

Copies in the Library

Location Call Number Status Location Service Notes
Stokes Library - Wallace Hall (SPR) Q180.55.S7 L58 2008 Browse related items Request

    Details

    Subject(s)
    Series
    Springer series in statistics [More in this series]
    Summary note
    "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."--Back cover.
    Bibliographic references
    Includes bibliographical references (p. [313]-332) and indexes.
    Contents
    • 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.
    ISBN
    • 9780387952307 ((alk. paper))
    • 0387952306 ((alk. paper))
    • 0387763694 ((pbk.))
    • 9780387763699 ((pbk.))
    OCLC
    191760006
    International Article Number
    • 9780387763699
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