Overview
- Explores the development and use of the modeling and computational capabilities in the Maple-based APPL programing language to solve real and important problems in probability
- Highlights the uses of symbolic algebra with probabilistic/stochastic applications in variety of contexts
- Authors are distinguished leaders in the field and development of computational methods for solving problems expressed using probability models
- Includes supplementary material: sn.pub/extras
Part of the book series: International Series in Operations Research & Management Science (ISOR, volume 247)
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Table of contents (15 chapters)
Keywords
About this book
Computational Probability Applications is comprised of fifteen chapters, each presenting a specific application of computational probability using the APPL modeling and computer language. The chapter topics include using inverse gamma as a survival distribution, linear approximations of probability density functions, and also moment-ratio diagrams for univariate distributions. These works highlight interesting examples, often done by undergraduate students and graduate students that can serve as templates for future work. In addition, this book should appeal to researchers and practitioners in a range of fields including probability, statistics, engineering, finance, neuroscience, and economics.
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Editors and Affiliations
About the editors
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 Applications
Editors: Andrew G. Glen, Lawrence M. Leemis
Series Title: International Series in Operations Research & Management Science
DOI: https://doi.org/10.1007/978-3-319-43317-2
Publisher: Springer Cham
eBook Packages: Business and Management, Business and Management (R0)
Copyright Information: Springer International Publishing Switzerland 2017
Hardcover ISBN: 978-3-319-43315-8Published: 16 December 2016
Softcover ISBN: 978-3-319-82788-9Published: 04 July 2018
eBook ISBN: 978-3-319-43317-2Published: 01 December 2016
Series ISSN: 0884-8289
Series E-ISSN: 2214-7934
Edition Number: 1
Number of Pages: X, 256
Number of Illustrations: 68 b/w illustrations, 10 illustrations in colour
Topics: Operations Research/Decision Theory, Statistics and Computing/Statistics Programs, Probability Theory and Stochastic Processes