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International Series in Operations Research & Management Science

Computational Probability

Algorithms and Applications in the Mathematical Sciences

Authors: Drew, J.H., Evans, D.L., Glen, A.G., Leemis, L.M.

  • New edition includes the latest advancements and developments in computational probability involving the APPL language
  • Focuses on two types of problems: algorithms for continuous random variables and algorithms for discrete random variables
  • New chapters cover the transformation of bivariate random variables and computational probability applications in time series analysis, as well as queuing theory 
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Buy this book

eBook $119.00
price for USA in USD (gross)
  • ISBN 978-3-319-43323-3
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $159.99
price for USA in USD
  • ISBN 978-3-319-43321-9
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
About this book

This new edition includes the latest advances and developments in computational probability involving A Probability Programming Language (APPL). The book examines and presents, in a systematic manner, computational probability methods that encompass data structures and algorithms. The developed techniques address problems that require exact probability calculations, many of which have been considered intractable in the past. The book addresses the plight of the probabilist by providing algorithms to perform calculations associated with random variables. 
Computational Probability: Algorithms and Applications in the Mathematical Sciences, 2nd Edition begins with an introductory chapter that contains short examples involving the elementary use of APPL. Chapter 2 reviews the Maple data structures and functions necessary to implement APPL. This is followed by a discussion of the development of the data structures and algorithms (Chapters 3–6 for continuous random variables and Chapters 7–9 for discrete random variables) used in APPL. The book concludes with Chapters 10–15 introducing a sampling of various applications in the mathematical sciences. This book should appeal to researchers in the mathematical sciences with an interest in applied probability and instructors using the book for a special topics course in computational probability taught in a mathematics, statistics, operations research, management science, or industrial engineering department.

About the authors

John Drew is a professor emeritus, retired in 2008 from the Department of Mathematics at The College of William & Mary in Williamsburg, Virginia, U.S.A. He received his BS in mathematics form Case Institute of Technology and his PhD in mathematics from the University of Minnesota. During his academic career he published 25 research papers in linear algebra, operations research, and computational probability.
Dr. Diane Evans is a professor in the Mathematics Department at Rose-Hulman Institute of Technology in Terre Haute, U.S.A. She received her BS and MA degrees in mathematics from The Ohio State University and her MS and PhD in operations research and applied science from The College of William and Mary. Diane was named in Princeton Review's 300 Best Professors in America and was selected as one of Microsoft's 365 "Heroes in Education" in 2012. During her 2015 sabbatical, she worked for Minitab creating educational materials for new statistics instructors. Her current research and teaching interests are in probability, statistics, quality control, and Six Sigma.  
Dr. Andrew Glen is a Professor Emeritus of Operations Research from the United States Military Academy, in West Point, NY. He is currently a visiting professor at The Colorado College in Colorado Springs, Colorado. He is a retired colonel from the US Army, and spend 16 years on faculty at West Point. He has published three books and dozens of scholarly articles, mostly on the subject of computational probability. His research and teaching interests are in computational probability and statistical modeling. 

Lawrence Leemis is a professor in the Department of Mathematics at The College of William & Mary in Williamsburg, Virginia, U.S.A. He received his BS and MS degrees in mathematics and his PhD in operations research from Purdue University. He has also taught courses at Purdue University, The University of Oklahoma, and Baylor University. He has served as Associate Editor for the IEEE Transactions on Reliability, Book Review Editor for the Journal of Quality Technology, and an Associate Editor for Naval Research Logistics. He has published six books and over 100 research articles, proceedings papers, and book chapters. His research and teaching interests are in reliability, simulation, and computational probability. 

Table of contents (15 chapters)

  • Computational Probability

    Drew, John H. (et al.)

    Pages 3-11

  • Maple for APPL

    Drew, John H. (et al.)

    Pages 13-30

  • Data Structures and Simple Algorithms

    Drew, John H. (et al.)

    Pages 33-45

  • Transformations of Random Variables

    Drew, John H. (et al.)

    Pages 47-56

  • Bivariate Transformations of Random Variables

    Drew, John H. (et al.)

    Pages 57-72

Buy this book

eBook $119.00
price for USA in USD (gross)
  • ISBN 978-3-319-43323-3
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $159.99
price for USA in USD
  • ISBN 978-3-319-43321-9
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Computational Probability
Book Subtitle
Algorithms and Applications in the Mathematical Sciences
Authors
Series Title
International Series in Operations Research & Management Science
Series Volume
246
Copyright
2017
Publisher
Springer International Publishing
Copyright Holder
Springer International Publishing AG
eBook ISBN
978-3-319-43323-3
DOI
10.1007/978-3-319-43323-3
Hardcover ISBN
978-3-319-43321-9
Series ISSN
0884-8289
Edition Number
2
Number of Pages
XI, 336
Number of Illustrations and Tables
60 b/w illustrations, 25 illustrations in colour
Topics