Monte Carlo: Concepts, Algorithms, and Applications (Springer Series in Operations Research and Financial Engineering)

George Fishman

ISBN 10: 038794527X / ISBN 13: 9780387945279

Published by Springer February 2003, 2003

About this Item

used hardcover copy, lacking a dust jacket (as issued). light shelfwear, corners perhaps slightly bumped, slight fading to spine. pages and binding are clean, straight, and tight. there are no marks to the text or other serious flaws.

Seller Inventory # 1287460

Bibliographic Details

• Title: Monte Carlo: Concepts, Algorithms, and Applications (Springer Series in Operations Research and Financial Engineering)
• Publisher: Springer February 2003
• Publication Date: 2003
• Language: English
• ISBN 10: 038794527X
• ISBN 13: 9780387945279
• Binding: Trade Paperback
• Condition: VG-
• Dust Jacket Condition: No Jacket
• Seller catalogs:
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About this title

Synopsis

This book provides an introduction to the Monte Carlo method suitable for a one-or two-semester course for graduate and advanced undergraduate students in the mathematical and engineering sciences. It also can serve as a reference for the professional analyst. In the past, my inability to provide students with a single­ source book on this topic for class and for later professional reference had left me repeatedly frustrated, and eventually motivated me to write this book. In addition to focused accounts of major topics, the book has two unifying themes: One concerns the effective use of information and the other concerns error control and reduction. The book describes how to incorporate information about a problem into a sampling plan in a way that reduces the cost of estimating its solution to within a specified error bound. Although exploiting special structures to reduce cost long has been a hallmark of the Monte Carlo method, the propen­ sity of users of the method to discard useful information because it does not fit traditional textbook models repeatedly has impressed me. The present account aims at reducing the impediments to integrating this information. Errors, both statistical and computational, abound in every Monte Carlo sam­ pling experiment, and a considerable methodology exists for controlling them.

From the Back Cover

This volume presents a comprehensive first course in the Monte Carlo method which will be suitable for graduate and undergraduate students in the mathematical sciences and engineering, principally operations research, statistics, mathematics, and computer science. The reader is assumed to have a sound understanding of calculus, introductory matrix analysis, probability, and intermediate statistics, but otherwise the book is self-contained. As well as a thorough exploration of the important concepts of the Monte Carlo method, the volume includes over 90 algorithms which allow the reader to move rapidly from the concepts to putting them into practice. The book also contains numerous exercises, many of them hands-on implementations of selected algorithms to demonstrate the application of these ideas in realistic settings. Software, freely available via ftp and portable across computing platforms, provides programs for pseudorandom number generation and statistical sample path data analysis. The software is suitable for use with the exercises as well as for more general applications. For professional mathematical scientists and engineers this book provides a ready reference to the Monte Carlo method, especially to implementable algorithms for performing sampling experiments on a computer and for analyzing their results.