Computational Probability (eBook, PDF) - Glen, Andrew G.; Evans, Diane L.; Drew, John H.; Leemis, Lawrence M.
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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…mehr

Produktbeschreibung
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. TOC:Introduction.- Computational Probability.- Maple for APPL.- Data Structures and Simple Algorithms.- Transformations of Random Variables.- Products of Random Variables.- Data Structures and Simple Algorithms.- Sums of Independent Random Variables.- Order Statistics.- Reliability and Survival Analysis.- Stochastic Simulation.- Other Applications.- References.- Index.

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  • Produktdetails
  • Verlag: Springer-Verlag GmbH
  • Erscheinungstermin: 08.01.2008
  • Englisch
  • ISBN-13: 9780387746760
  • Artikelnr.: 37287766
Autorenporträt
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.
Inhaltsangabe
Computational Probability.- Maple for APPL.- Data Structures and Simple Algorithms.- Transformations of Random Variables.- Bivariate Transformations of Random Variables.- Products of Random Variables.- Data Structures and Simple Algorithms.- Sums of Independent Discrete Random Variables.- Order Statistics for Random Sampling from Discrete Populations.- Reliability and Survival Analysis.- Symbolic ARMA Model Analysis.- Stochastic Simulation.- Transient Queueing Analysis.- Bayesian Applications.- Other Applications.