Computational Probability: Algorithms and Applications in the Mathematical Scien

Description: Computational Probability by John H. Drew, Diane L. Evans, Andrew G. Glen, Lawrence M. Leemis This new edition includes the latest advances and developments in computational probability involving A Probability Programming Language (APPL). FORMAT Paperback LANGUAGE English CONDITION Brand New Publisher Description 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. Back Cover 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. Author Biography 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 Reviews 300 Best Professors in America and was selected as one of Microsofts 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 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. Feature 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 Details ISBN3319827901 Author Lawrence M. Leemis Series International Series in Operations Research & Management Science ISBN-10 3319827901 ISBN-13 9783319827902 Format Paperback Subtitle Algorithms and Applications in the Mathematical Sciences DEWEY 519.2 Pages 336 Publisher Springer International Publishing AG Year 2018 Publication Date 2018-07-04 Imprint Springer International Publishing AG Place of Publication Cham Country of Publication Switzerland Short Title Computational Probability Language English Edition 2nd Series Number 246 UK Release Date 2018-07-04 Narrator Patrick Osborne Edited by Paolo Mele Birth 1974 Affiliation Massachusetts Institute of Technology Position journalist Edition Description Softcover reprint of the original 2nd ed. 2017 Alternative 9783319433219 Audience Professional & Vocational Illustrations 25 Illustrations, color; 60 Illustrations, black and white; XI, 336 p. 85 illus., 25 illus. in color. We've got this At The Nile, if you're looking for it, we've got it. 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