Elements of Applied Stochastic Processes (Probability & Mathematical Statistics Series)

This 3rd edition of the successful Elements of Applied Stochastic Processes improves on the last edition by condensing the material and organising it into a more teachable format. It provides more in-depth coverage of Markov chains and simple Markov process and gives added emphasis to statistical inference in stochastic processes.

• Integration of theory and application offers improved teachability
• Provides a comprehensive introduction to stationary processes and time series analysis
• Integrates a broad set of applications into the text
• Utilizes a wealth of examples from research papers and monographs

This revised and expanded edition of Elements of Applied Stochastic Processes offers wider coverage of the applications of stochastic processes in various fields. It develops basic concepts and techniques and brings together a sampling of their uses for solving problems arising in queueing, reliability, inventory and computer communications, social and behavioral processes, and business management and time series analysis. The book can be divided into two broad sections. Chapters 1 through 9 treat the theory of Markov, renewal, and stationary processes. Chapters 10 through 21 deal with applications and include six new chapters. In addition to the incorporation of new material in all chapters, major changes in the first half include: the consolidation of the chapter on two-state Markov processes with the chapter on Finite Markov Chains; a new section on graph theoretic methods; new chapters on time-dependent and limiting behavior and on special topics and inference in finite Markov chains; the expansion of the material on stationary processes to include ergodic theorems, spectral density, and linear filters; and the addition of over 200 exercises in the first nine chapters, with answers at the end of the book. Completely new chapters in the second half of the book include: queueing networks, communication and information systems, inventory and storage processes, combat models, Markov models in biological sciences, and stochastic models in traffic flow theory and geological sciences. In addition, the chapter on time series analysis has been updated and expanded, and has been moved to the end of the book to maintain the continuity of treatment of similar models. Elements of Applied Stochastic Processes, 2nd Edition is useful as a classroom text for industrial and systems engineering, operations research, statistics, business, economics, mathematics, and computer science students. It serves as a reference for researchers who use probability models based on Markov processes, renewal processes and time series, and aids consultants who solve problems involving probability models in the societal, industrial, business, and government sectors. Additionally, the up-to-date list of references and a list of articles and books for further reading in applied areas will be a major resource for the applied scientist.