A Course in Stochastic Processes: Stochastic Models And Statistical Inference

Preface. 1. Basic Probability Background. 2. Modeling Random Phenomena. 3. Discrete-Time Markov Chains. 4. Poisson Processes. 5. Continuous-Time Markov Chains. 6. Random Walks. 7. Renewal Theory. 8. Queueing Theory. 9. Stationary Processes. 10. ARMA model. 11. Discrete-Time Martingales. 12. Brownian Motion and Diffusion Processes. 13. Statistics for Poisson Processes. 14. Statistics of Discrete-Time Stationary Processes. 15. Statistics of Diffusion Processes. A. Measure and Integration. B. Banach and Hilbert Spaces. List of Symbols. Bibliography. Partial Solutions to Selected Exercises. Index.