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International Series in Operations Research & Management Science

Computational Probability Applications

Editors: Glen, Andrew G., Leemis, Lawrence M. (Eds.)

  • 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
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eBook $119.00
price for USA in USD (gross)
  • ISBN 978-3-319-43317-2
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $159.99
price for USA in USD
  • ISBN 978-3-319-43315-8
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $159.99
price for USA in USD
  • ISBN 978-3-319-82788-9
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
About this book

This focuses on the developing field of building probability models with the power of symbolic algebra systems. The book combines the uses of symbolic algebra with probabilistic/stochastic application and highlights the applications in a variety of contexts. The research explored in each chapter is unified by the use of A Probability Programming Language (APPL) to achieve the modeling objectives. APPL, as a research tool, enables a probabilist or statistician the ability to explore new ideas, methods, and models. Furthermore, as an open-source language, it sets the foundation for future algorithms to augment the original code. 
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.

About the authors

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.

Reviews

“This volume successfully merges the use of symbolic algebra with stochastic applications and displays its applications in a host of situations. … The book organized sequentially, well structured, and chapters are self-contained. … The book is a good source as a reference book in a multitude fields. … this is a good contribution, providing up-to-date coverage on selected topics in a logical and systematic manner. Variability and diversity in research is the spice of the life!” (S. Ejaz Ahmed, Technometrics, Vol. 59 (3), July, 2017)


Table of contents (15 chapters)

  • Accurate Estimation with One Order Statistic

    Glen, Andrew G.

    Pages 1-13

  • On the Inverse Gamma as a Survival Distribution

    Glen, Andrew G.

    Pages 15-30

  • Order Statistics in Goodness-of-Fit Testing

    Glen, Andrew G. (et al.)

    Pages 31-39

  • The “Straightforward” Nature of Arrival Rate Estimation?

    Barr, Donald R. (et al.)

    Pages 41-50

  • Survival Distributions Based on the Incomplete Gamma Function Ratio

    Glen, Andrew G. (et al.)

    Pages 51-58

Buy this book

eBook $119.00
price for USA in USD (gross)
  • ISBN 978-3-319-43317-2
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $159.99
price for USA in USD
  • ISBN 978-3-319-43315-8
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $159.99
price for USA in USD
  • ISBN 978-3-319-82788-9
  • 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 Applications
Editors
  • Andrew G. Glen
  • Lawrence M. Leemis
Series Title
International Series in Operations Research & Management Science
Series Volume
247
Copyright
2017
Publisher
Springer International Publishing
Copyright Holder
Springer International Publishing Switzerland
eBook ISBN
978-3-319-43317-2
DOI
10.1007/978-3-319-43317-2
Hardcover ISBN
978-3-319-43315-8
Softcover ISBN
978-3-319-82788-9
Series ISSN
0884-8289
Edition Number
1
Number of Pages
X, 256
Number of Illustrations
68 b/w illustrations, 10 illustrations in colour
Topics