A First Course in Stochastic Processes, Second Edition (Hardback)

Condition

LIKE NEW: This book is in excellent, like-new condition. It was printed on acid-free paper.

Product Details

From the Preface to the First Edition: "Stochastic processes concern sequences of events governed by probabilistic laws. Many applications of stochastic processes occur in physics, engineering, biology, medicine, psychology, and other disciplines, as well as in other branches of mathematical analysis. The purpose of this book is to provide an introduction to the many specialized treatises on stochastic processes. Specifically, I have endeavored to achieve three objectives: (1) to present a systematic introductory account of several principal areas in stochastic processes, (2) to attract and interest students of pure mathematics in the rich diversity of applications of stochastic processes, and (3) to make the student who is more concerned with application aware of the relevance and importance of the mathematical subtleties underlying stochastic processes.

"The examples in this book are drawn mainly from biology and engineering but there is an emphasis on stochastic structures that are of mathematical interest or of importance in more than one discipline. A number of concepts and problems that are currently prominent in probability research are discussed and illustrated."

From the Preface (to the Second Edition): "We have made three main kinds of changes. First, we have enlarged on the topics treated in the first edition. Second, we have added many exercises and problems at the end of each chapter. Third, and most important, we have supplied, in new chapters, broad introductory discussions of several classes of stochastic processes not dealt with in the first edition, notably martingales, renewal and fluctuation phenomena associated with random sums, stationary stochastic processes, and diffusion theory."

BRIEF CONTENTS

Each chapter includes Elementary Problems, Problems, Notes, and References.

1. Elements of Stochastic Processes
2. Markov Chains
3. The Basic Limit Theorem of Markov Chains and Applications
4. Classical Examples of Continuous Time Markov Chains
5. Renewal Processes
6. Martingales
7. Brownian Motion
8. Branching Processes
9. Stationary Processes

The book ends with Appendix: Review of Matrix Analysis and an Index.