Mathematics

Probability Theory & Applications

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What Makes Variables Random: Probability for the Applied Researcher

Peter J. Veazie
May 03, 2017

What Makes Variables Random: Probability for the Applied Researcher provides an introduction to the foundations of probability that underlie the statistical analyses used in applied research. By explaining probability in terms of measure theory, it gives the applied researchers a conceptual...

Reliability Models for Engineers and Scientists

Mark P. Kaminskiy
March 29, 2017

A discussion of the basic reliability concepts and models, Reliability Models for Engineers and Scientists demystifies modern mathematical reliability models. Requiring very little mathematical background on the reader’s part, this concise book introduces the models by focusing on their physical...

Change-Point Analysis in Nonstationary Stochastic Models

Boris Brodsky
March 23, 2017

This book covers the development of methods for detection and estimation of changes in complex systems. These systems are generally described by nonstationary stochastic models, which comprise both static and dynamic regimes, linear and nonlinear dynamics, and constant and time-variant structures...

Stochastic Processes: From Applications to Theory

Pierre Del Moral, Spiridon Penev
December 19, 2016

Unlike traditional books presenting stochastic processes in an academic way, this book includes concrete applications that students will find interesting such as gambling, finance, physics, signal processing, statistics, fractals, and biology. Written with an important illustrated guide in the...

Elementary Probability with Applications, Second Edition

Larry Rabinowitz
December 13, 2016

Elementary Probability with Applications, Second Edition shows students how probability has practical uses in many different fields, such as business, politics, and sports. In the book, students learn about probability concepts from real-world examples rather than theory. The text explains how...

Reliability Engineering and Risk Analysis: A Practical Guide, Third Edition

Mohammad Modarres, Mark P. Kaminskiy, Vasiliy Krivtsov
December 01, 2016

This undergraduate and graduate textbook provides a practical and comprehensive overview of reliability and risk analysis techniques. Written for engineering students and practicing engineers, the book is multi-disciplinary in scope. The new edition has new topics in classical confidence interval...

Mean Field Simulation for Monte Carlo Integration

Pierre Del Moral
October 26, 2016

In the last three decades, there has been a dramatic increase in the use of interacting particle methods as a powerful tool in real-world applications of Monte Carlo simulation in computational physics, population biology, computer sciences, and statistical machine learning. Ideally suited to...

Monte-Carlo Methods and Stochastic Processes: From Linear to Non-Linear

Emmanuel Gobet
August 01, 2016

Developed from the author’s course at the Ecole Polytechnique, Monte-Carlo Methods and Stochastic Processes: From Linear to Non-Linear focuses on the simulation of stochastic processes in continuous time and their link with partial differential equations (PDEs). It covers linear and nonlinear...

Reliability Assessments: Concepts, Models, and Case Studies

Franklin Richard Nash, Ph.D.
July 06, 2016

This book provides engineers and scientists with a single source introduction to the concepts, models, and case studies for making credible reliability assessments. It satisfies the need for thorough discussions of several fundamental subjects. Section I contains a comprehensive overview of...

Applied Probability and Stochastic Processes, Second Edition

Frank Beichelt
May 03, 2016

Applied Probability and Stochastic Processes, Second Edition presents a self-contained introduction to elementary probability theory and stochastic processes with a special emphasis on their applications in science, engineering, finance, computer science, and operations research. It covers the...

Essentials of Probability Theory for Statisticians

Michael A. Proschan, Pamela A. Shaw
March 15, 2016

Essentials of Probability Theory for Statisticians provides graduate students with a rigorous treatment of probability theory, with an emphasis on results central to theoretical statistics. It presents classical probability theory motivated with illustrative examples in biostatistics, such as...

Perfect Simulation

Mark L. Huber
November 19, 2015

Exact sampling, specifically coupling from the past (CFTP), allows users to sample exactly from the stationary distribution of a Markov chain. During its nearly 20 years of existence, exact sampling has evolved into perfect simulation, which enables high-dimensional simulation from interacting...

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