Authors:
- This is an expository monograph with a downloadable modeling language, APPL, that will be used across the Applied Sciences domains including OR/MS, Applied Probability, Engineering, Statistics, Economics, and Applied Mathematics. It will be used by practitioners, as well as academic researchers and students
- The book package will sell nicely in both the academic and practitioner areas. Moreover, the software will motivate the sales of the book package. The authors, through their APPL software, have some very good practitioner contacts worldwide.
Part of the book series: International Series in Operations Research & Management Science (ISOR, volume 117)
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Table of contents (11 chapters)
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Front Matter
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Introduction
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Algorithms for Continuous Random Variables
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Algorithms for Discrete Random Variables
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Back Matter
About this book
Computational probability is a set of stochastic methods that has emerged over the past decade that allow researchers and students to solve problems that require exact probability calculations previously considered arduous or intractable.
Computational Probability is the first book that examines and organizes these computational methods into a systematic treatment. The book is structured around the two categories of problems: (1) “Algorithms for Continuous Random Variables” has chapters on data structures and algorithms, transformations of random variables, and products of independent random variables. (2) “Algorithms for Discrete Random Variables” includes data structures and algorithms, sums of independent random variables, and order statistics. The book includes three chapters that emphasize survival analysis and simulation applications. The APPL computational modeling language that gives probabilists a strong software resource for non-trivial problems is available at www.APPLsoftware.com.
Reviews
From the reviews:
"The monograph is devoted to the use of a computer algebra system to solve problems in operations research and probability. … The presented monograph will be of interest for all researchers and specialists that are working in the mathematical sciences … . It will be very useful for the lecturers, which could use it for the preparation of special topics courses in computational probability … . The intended audience for the presented monograph includes researchers, MS students, PhD students, and advanced practitioners … ." (Tzvetan Semerdjiev, Zentralblatt MATH, Vol. 1145, 2008)
"The text is … an introduction to a computer language called A Probability Programming Language (APPL), specially created by the authors to make it easy for statisticians and operational researchers to carry out complex manipulations involving probability distributions. … I would recommend this book to anyone working with probability distributions. … the book could certainly be of use to operational research practitioners working in ‘hard’ OR fields where complex probabilistic models are needed." (John Smith, Journal of the Operational Research society, Vol. 60 (7), 2009)
Authors and Affiliations
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College of William and Mary, Williamsburg, USA
John H. Drew
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Rose-Hulman Institute of Technology, Terre Haute, USA
Diane L. Evans
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United States Military Academy, West Point, USA
Andrew G. Glen
Bibliographic Information
Book Title: Computational Probability
Book Subtitle: Algorithms and Applications in the Mathematical Sciences
Authors: John H. Drew, Diane L. Evans, Andrew G. Glen, Lawrence M. Leemis
Series Title: International Series in Operations Research & Management Science
DOI: https://doi.org/10.1007/978-0-387-74676-0
Publisher: Springer New York, NY
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer-Verlag US 2008
eBook ISBN: 978-0-387-74676-0Published: 08 January 2008
Series ISSN: 0884-8289
Series E-ISSN: 2214-7934
Edition Number: 1
Number of Pages: X, 222
Topics: Applications of Mathematics, Operations Research/Decision Theory, Probability Theory and Stochastic Processes, Mathematical and Computational Engineering, Computational Mathematics and Numerical Analysis, Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences