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Friday, May 22, 2020 | History

5 edition of Monte Carlo strategies in scientific computing found in the catalog.

Monte Carlo strategies in scientific computing

Jun S. Liu

Monte Carlo strategies in scientific computing

by Jun S. Liu

  • 214 Want to read
  • 33 Currently reading

Published by Springer in New York .
Written in English

    Subjects:
  • Science -- Statistical methods,
  • Monte Carlo method

  • Edition Notes

    Includes bibliographical references (p. [313]-332) and indexes.

    StatementJun S. Liu.
    SeriesSpringer series in statistics
    Classifications
    LC ClassificationsQ180.55.S7 L58 2001, Q180.55.S7 L58 2001
    The Physical Object
    Paginationxvi, 343 p. :
    Number of Pages343
    ID Numbers
    Open LibraryOL18162683M
    ISBN 100387952306
    LC Control Number00069243

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Monte Carlo strategies in scientific computing by Jun S. Liu Download PDF EPUB FB2

Monte Carlo Strategies in Scientific Computing offers a large variety of methods and examples. Those interested in using MC to solve difficult problems will find many ideas, collected from a variety of disciplines, and references for further study." (Tim Hesterberg, Technometrics, Vol.

44 (4), )Cited by: Monte Carlo Strategies in Scientific Computing byLiu [Liu] on *FREE* shipping on qualifying offers. Monte Carlo Strategies in Scientific Computing byLiu/5(7). Monte Carlo Strategies in Scientific Computing The author is a leading researcher in a very active area of research.

Emphasis is on making these methods accessible to scientists who want to apply them. Includes examples from artificial intelligence, computational biology, computer vision and Brand: Springer-Verlag New York. Monte Carlo Strategies in Scientific Computing. 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/5(8).

The coverage is up-to-date and comprehensive, and so the book is a good resource for people conducting research on Monte Carlo methods. The book would be an excellent supplementary text for a course in scientific computing." (SIAM Review) "The strength of this book is in bringing together advanced Monte Carlo (MC) methods developed in many disciplines.

The book is well organized; the flow of topics follows a logical development. The coverage is up-to-date and comprehensive, and so the book is a good resource for people conducting research on Monte Carlo methods.

The book would Monte Carlo strategies in scientific computing book an excellent supplementary text for a course in scientific computing ." (SIAM Review).

The Need of Monte Carlo Techniques 1 Scope and Outline of the Book 3 Computations in Statistical Physics 7 Molecular Structure Simulation 9. The previous chapter outlines a general Monte Carlo framework based on the sequential buildup strategy. Several essential elements are (a) the choice of the trial densities, (b) the resampling method, (c) the marginalization strategy, and (d) the rejection control.

This book represents the refereed proceedings of the Tenth International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing that was held at the University of New South Wales (Australia) in February These biennial conferences are major events for Monte Carlo and.

This paperback edition is a reprint of the Springer edition. This book provides a self-contained and up-to-date treatment of the Monte Carlo method and develops a common fram5/5(1). Monte Carlo Strategies in Scientific Computing by Jun S Liu available in Trade Paperback onalso read synopsis and reviews.

This book provides an up-to-date treatment of the Monte Carlo method and develops a common framework. Monte Carlo Strategies in Scientific Computing Jun S. Liu (auth.) This paperback edition is a reprint of the Springer edition.

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.

Monte Carlo strategies in scientific computing. [Jun S Liu] MATHEMATICAL REVIEWS "This book is an excellent survey of current Monte Carlo methods.

A strength of the book is the inclusion of a number of applications to current name\/a> \" Monte Carlo strategies in scientific computing\/span>\" ; \u00A0\u00A0\u00A0\n schema:productID\/a. Monte Carlo strategies in scientific computing. [Jun S Liu] -- "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.

"The strength of this book is in bringing together advanced Monte Carlo (MC) methods developed in many disciplines. Throughout the book are examples of techniques invented, or /5(8). Monte Carlo Strategies in Scientific Computing - Jun S.

Liu, Jun S. Liu, S. Liu Jun - Google Books This book provides a self-contained and up-to-date treatment of the Monte Carlo method and. Ebooks list page: ; Monte Carlo Strategies in Scientific Computing By Jun S. Liu; [PDF] Random Number Generation and Monte Carlo Methods (Statistics and Computing); Random Number Generation and Monte Carlo Methods (Statistics and Computing) (Repost); Random Number Generation and Monte Carlo Methods (Statistics and Computing).

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Springer Series in Statistics by Liu, Jun S.: and a great selection of related books, art and collectibles available now at. READ book Monte Carlo Strategies in Scientific Computing (Springer Series in Statistics) READ.The Monte Carlo method is a computer-based statistical sampling approach for solving numerical problems concerned with a complex system.

The methodology was initially developed in the field of statistical physics during the early days of electronic computing () and has now been adopted by researchers in almost all scientific fields Author: Jun S.

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