Overview
- 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
- Includes supplementary material: sn.pub/extras
Part of the book series: International Series in Operations Research & Management Science (ISOR, volume 246)
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Table of contents (15 chapters)
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Front Matter
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Introduction
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Front Matter
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Algorithms for Continuous Random Variables
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Front Matter
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Algorithms for Discrete Random Variables
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Front Matter
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Keywords
About this book
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.
Authors and Affiliations
About the authors
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.
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/10.1007/978-3-319-43323-3
Publisher: Springer Cham
eBook Packages: Business and Management, Business and Management (R0)
Copyright Information: Springer International Publishing AG 2017
Hardcover ISBN: 978-3-319-43321-9Published: 22 December 2016
Softcover ISBN: 978-3-319-82790-2Published: 04 July 2018
eBook ISBN: 978-3-319-43323-3Published: 15 December 2016
Series ISSN: 0884-8289
Series E-ISSN: 2214-7934
Edition Number: 2
Number of Pages: XI, 336
Number of Illustrations: 60 b/w illustrations, 25 illustrations in colour
Topics: Operations Research/Decision Theory, Statistics and Computing/Statistics Programs, Probability Theory and Stochastic Processes