Description

About the Book:

The book aims at the level between elementary probability texts and advanced works on stochastic processes. The prerequisites are a course on elementary probability theory and statistics, and a course on advanced calculus. The theoretical results developed have been followed by a large number of illustrative (worked) examples. These have been supplemented by numerous exercises, answers to most of which are also given. It is expected to suit as a text for advanced undergraduate, postgraduate and research level courses in Applied Mathematics, Statistics, Operations Research, Computer Science, different branches of Engineering, Telecommunications, Business and Management, Economics, Life Sciences and so on.

A review of the Ist edition of the book in the American Mathematical Monthly (December 1982) gives this book special positive emphasis as a textbook as “the clear choice” amongst about a dozen or more texts (

Contents:

Random Variables and Stochastic Processes

Markov Chains

Markov Processes with Discrete State Space: Poisson Process and its Extensions

Markov Processes with Continuous State Space

Martingales

Renewal Processes and Theory

Markov Renewal and Semi-Markov Processes

Stationary Processes and Time Series

Branching Processes

Applications in Stochastic Models

Simulation