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Monte Carlo (Springer Series in Operations Research)

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Monte Carlo (Springer Series in Operations Research) Cover

 

Synopses & Reviews

Publisher Comments:

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 in 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 implementatable algorithms for performing sampling experiments on a computer and for analyzing their results.

Synopsis:

Apart from a thorough exploration of all the important concepts, this volume includes over 75 algorithms, ready for putting into practice. The book also contains numerous hands-on implementations of selected algorithms to demonstrate applications in realistic settings. Readers are assumed to have a sound understanding of calculus, introductory matrix analysis, and intermediate statistics, but otherwise the book is self-contained. Suitable for graduates and undergraduates in mathematics and engineering, in particular operations research, statistics, and computer science.

Table of Contents

Preface * Selected Notation * 1 Introduction * 2 Estimating Volume and Count * 3 Generating Samples * 4 Increasing Efficiency * 5 Random Tours * 6 Designing and Analyzing Sample Paths * 7 Generating Pseudorandom Numbers * Author Index * Subject Index

Product Details

ISBN:
9780387945279
Author:
Fishman, George
Author:
Fishman
Publisher:
Springer
Location:
New York, NY
Subject:
Statistics
Subject:
Probability
Subject:
Operations Research
Subject:
Monte carlo method
Subject:
Probability & Statistics - General
Subject:
Mathematics | Probability and Statistics
Subject:
Operations Research/Decision Theory
Subject:
Statistics for Business/Economics/Mathematical Finance/Insurance
Subject:
Operation Research/Decision Theory
Subject:
Economics
Subject:
Language, literature and biography
Subject:
mathematics and statistics
Subject:
Economics_xStatistics
Copyright:
Edition Number:
2
Edition Description:
1st ed. 1996. Corr. 4th printing
Series:
Springer Series in Operations Research and Financial Engineering
Series Volume:
103-646
Publication Date:
19960425
Binding:
HARDCOVER
Language:
English
Illustrations:
Y
Pages:
723
Dimensions:
235 x 178 mm 1320 gr

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Product details 723 pages Springer-Verlag - English 9780387945279 Reviews:
"Synopsis" by , Apart from a thorough exploration of all the important concepts, this volume includes over 75 algorithms, ready for putting into practice. The book also contains numerous hands-on implementations of selected algorithms to demonstrate applications in realistic settings. Readers are assumed to have a sound understanding of calculus, introductory matrix analysis, and intermediate statistics, but otherwise the book is self-contained. Suitable for graduates and undergraduates in mathematics and engineering, in particular operations research, statistics, and computer science.
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