An Introduction to Stochastic Modeling

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Gulf Professional Publishing, 1998 - Mathematics - 631 pages
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Serving as the foundation for a one-semester course in stochastic processes for students familiar with elementary probability theory and calculus, Introduction to Stochastic Modeling, Third Edition, bridges the gap between basic probability and an intermediate level course in stochastic processes. The objectives of the text are to introduce students to the standard concepts and methods of stochastic modeling, to illustrate the rich diversity of applications of stochastic processes in the applied sciences, and to provide exercises in the application of simple stochastic analysis to realistic problems.


* Realistic applications from a variety of disciplines integrated throughout the text
* Plentiful, updated and more rigorous problems, including computer "challenges"
* Revised end-of-chapter exercises sets-in all, 250 exercises with answers
* New chapter on Brownian motion and related processes
* Additional sections on Matingales and Poisson process
* Solutions manual available to adopting instructors
 

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User Review - Flag as inappropriate

Excellent textbook. Markov Chains are extensively treated,
analysis are specially placed and real problems emerge frequently.
But, there is also a lack of sensibility with difficult of problems,
where the problems section arise there's no indicator of how much
difficult it is.

Contents

Conditional Probability and Conditional
57
Introduction
95
The Long Run Behavior of Markov Chains
199
Poisson Processes
267
Continuous Time Markov Chains
333
Renewal Phenomena
419
The Asymptotic Behavior of Renewal Processes
437
Generalizations and Variations on Renewal Processes
447
Brownian Motion with Drift
508
The OrnsteinUhlenbeck Process
524
Queueing Systems
541
Poisson Arrivals Exponential Service Times
547
General Service Time Distributions
558
Variations and Extensions
567
Open Acyclic Queueing Networks
581
General Open Networks
592

Discrete Renewal Theory
457
Brownian Motion and Related Processes
473
The Maximum Variable and the Reflection Principle
491
Variations and Extensions
498
Further Reading
601
Answers to Exercises
603
Index
625
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