9780444515759-0444515755-Exploring Monte Carlo Methods

Exploring Monte Carlo Methods

ISBN-13: 9780444515759
ISBN-10: 0444515755
Edition: 1
Author: J. Kenneth Shultis, William L. Dunn
Publication date: 2011
Publisher: Elsevier Science
Format: Hardcover 398 pages
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Book details

ISBN-13: 9780444515759
ISBN-10: 0444515755
Edition: 1
Author: J. Kenneth Shultis, William L. Dunn
Publication date: 2011
Publisher: Elsevier Science
Format: Hardcover 398 pages

Summary

Exploring Monte Carlo Methods (ISBN-13: 9780444515759 and ISBN-10: 0444515755), written by authors J. Kenneth Shultis, William L. Dunn, was published by Elsevier Science in 2011. With an overall rating of 3.7 stars, it's a notable title among other Applied (Mathematics) books. You can easily purchase or rent Exploring Monte Carlo Methods (Hardcover) from BooksRun, along with many other new and used Applied books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.3.

Description

Exploring Monte Carlo Methods is a basic text that describes the numerical methods that have come to be known as "Monte Carlo." The book treats the subject generically through the first eight chapters and, thus, should be of use to anyone who wants to learn to use Monte Carlo. The next two chapters focus on applications in nuclear engineering, which are illustrative of uses in other fields. Five appendices are included, which provide useful information on probability distributions, general-purpose Monte Carlo codes for radiation transport, and other matters. The famous "Buffon’s needle problem" provides a unifying theme as it is repeatedly used to illustrate many features of Monte Carlo methods.

This book provides the basic detail necessary to learn how to apply Monte Carlo methods and thus should be useful as a text book for undergraduate or graduate courses in numerical methods. It is written so that interested readers with only an understanding of calculus and differential equations can learn Monte Carlo on their own. Coverage of topics such as variance reduction, pseudo-random number generation, Markov chain Monte Carlo, inverse Monte Carlo, and linear operator equations will make the book useful even to experienced Monte Carlo practitioners.

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