Computational Probability Applications

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.

• Accurate Estimation with One Order Statistic.- On the Inverse Gamma as a Survival Distribution.- Order Statistics in Goodness-of-Fit Testing.- The "Straightforward" Nature of Arrival Rate Estimation?.- Survival Distributions Based on the Incomplete Gamma Function Ratio.- An Inference Methodology for Life Tests with Full Samples or Type II Right Censoring.- Maximum Likelihood Estimation Using Probability Density Functions of Order Statistics.- Notes on Rank Statistics.- Control Chart Constants for Non-Normal Sampling.- Linear Approximations of Probability Density Functions.- Univariate Probability Distributions.- Moment-Ratio Diagrams for Univariate Distributions.- The Distribution of the Kolmogorov-Smirnov, Cramer-von Mises, and Anderson-Darling Test Statistics for Exponential Populations with Estimated Parameters.- Parametric Model Discrimiation for Heavily Censored Survival Data.- Lower Confidence Bounds for System Reliability from Binary Failure Data Using Bootstrapping.

“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)