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Monte Carlo strategies in scientific computing /

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This paperback edition is a reprint of the 2001 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. Given the interdisciplinar...

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Bibliographic Details
Main Author: Liu, Jun S.
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: New York : Springer, 2008.
Series:Springer series in statistics.
Subjects:
Science > Statistical methods.
Monte Carlo method.
Monte-Carlo-Simulation.
Wissenschaftliches Rechnen.
Electronic books.
Online Access:Connect to the full text of this electronic book
Table of Contents:
  • Introduction and Examples
  • Basic Principles: Rejection, Weighting, and Others
  • Theory of Sequential Monte Carlo
  • Sequential Monte Carlo in Action
  • Metropolis Algorithm and Beyond
  • The Gibbs Sampler
  • Cluster Algorithms for the Ising Model
  • General Conditional Sampling
  • Molecular Dynamics and Hybrid Monte Carlo
  • Multilevel Sampling and Optimization Methods
  • Population-Based Monte Carlo Methods
  • Markov Chains and Their Convergence
  • Selected Theoretical Topics
  • Basics in Probability and Statistics
  • References
  • Author Index
  • Subject Index.