Skip to search
Skip to main content
Catalog
Help
Feedback
Your Account
Library Account
Bookmarks
(
0
)
Search History
Search in
Keyword
Title (keyword)
Author (keyword)
Subject (keyword)
Title starts with
Subject (browse)
Author (browse)
Author (sorted by title)
Call number (browse)
search for
Search
Advanced Search
Bookmarks
(
0
)
Princeton University Library Catalog
Start over
Cite
Send
to
SMS
Email
EndNote
RefWorks
RIS
Printer
Bookmark
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
Online Content
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)
Science
—
Statistical methods
[Browse]
Monte Carlo method
[Browse]
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.
Show 15 more Contents items
ISBN
9780387952307 ((alk. paper))
0387952306 ((alk. paper))
0387763694 ((pbk.))
9780387763699 ((pbk.))
OCLC
191760006
International Article Number
9780387763699
Statement on language in description
Princeton University Library aims to describe library materials in a manner that is respectful to the individuals and communities who create, use, and are represented in the collections we manage.
Read more...
Other views
Staff view
Ask a Question
Suggest a Correction
Report Harmful Language
Supplementary Information