An Introduction to Stochastic Modeling
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
What people are saying - Write a review
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.
Conditional Probability and Conditional
The Long Run Behavior of Markov Chains
Continuous Time Markov Chains
The Asymptotic Behavior of Renewal Processes
Generalizations and Variations on Renewal Processes
Brownian Motion with Drift
The OrnsteinUhlenbeck Process
Poisson Arrivals Exponential Service Times
General Service Time Distributions
Variations and Extensions
Open Acyclic Queueing Networks
General Open Networks