Elements of Applied Stochastic Processes

Bhat, U. Narayan / Miller, Gregory K.

Wiley Series in Probability and Statistics

3. Edition September 2002
XVI, 472 Pages, Hardcover
Textbook

ISBN: 978-0-471-41442-1

John Wiley & Sons

Short Description

This third edition of the successful Elements of Applied Stochastic Processes improves on the last edition by condensing the material and organizing 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.

Preface.

Stochastic Processes: Description and Definition.

Markov chains.

Irreducible Markov Chains with Ergodic States.

Branching Processes and Other Special Topics.

Statistical Inference for Markov Chains.

Applied Markov Chains.

Simple Markov Processes.

Statistical Inference for Simple Markov Processes.

Applied Markov Processes.

Renewal Processes.

Stationary Processes and Time Series Analysis.

Simulation and Markov Chain Monte Carlo.

Answers to Selected Exercises.

Appendix.

Author Index.

Subject Index.

U. NARAYAN BHAT, PhD, is Professor of Statistical Science and Operations Research as well as the Dean of Research and Graduate Studies at Southern Methodist University.
GREGORY K. MILLER, PhD, is Associate Professor of Statistics at Stephen F. Austin State University.