Verkauf durch Sack Fachmedien

Liu

Monte Carlo Strategies in Scientific Computing

Medium: Buch
ISBN: 978-0-387-76369-9
Verlag: Springer
Erscheinungstermin: 04.01.2008
Lieferfrist: bis zu 10 Tage

A large number of scientists and engineers use Monte Carlo simulation as an essential tool in their work. This paperback edition (a reprint of the 2001 Springer edition) provides an up-to-date and self-contained summary of recent research results. 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 a textbook for a graduate-level course on Monte Carlo methods. Many problems discussed in the later chapters can be potential thesis topics for masters’ or Ph.D. students in statistics or computer science departments.


Produkteigenschaften


  • Artikelnummer: 9780387763699
  • Medium: Buch
  • ISBN: 978-0-387-76369-9
  • Verlag: Springer
  • Erscheinungstermin: 04.01.2008
  • Sprache(n): Englisch
  • Auflage: 1. Auflage 2001, 2. printing 2008
  • Serie: Springer Series in Statistics
  • Produktform: Kartoniert
  • Gewicht: 1130 g
  • Seiten: 344
  • Format (B x H x T): 154 x 236 x 22 mm
  • Ausgabetyp: Kein, Unbekannt
Autoren/Hrsg.

Autoren

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.- A.1 Basic Probability Theory.- A.1.1 Experiments, events, and probability.- A.1.2 Univariate random variables and their properties.- A.1.3 Multivariate random variable.- A.1.4 Convergence of random variables.- A.2 Statistical Modeling and Inference.- A.2.1 Parametric statistical modeling.- A.2.2 Frequentist approach to statistical inference.- A.2.3 Bayesian methodology.- A.3 Bayes Procedure and Missing Data Formalism.- A.3.1 The joint and posterior distributions.- A.3.2 The missing data problem.- A.4 The Expectation-Maximization Algorithm.- References.- Author Index.