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Introduction to Stochastic Processes



Pub. Date:
Dover Publications
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This is the Reprint edition with a publication date of 2/20/2013.
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This clear presentation of the most fundamental models of random phenomena employs methods that recognize computer-related aspects of theory. Topics include probability spaces and random variables, expectations and independence, Bernoulli processes and sums of independent random variables, Poisson processes, Markov chains and processes, and renewal theory. Includes an introduction to basic stochastic processes. 1975 edition.

Table of Contents

1. Probability Spaces and Random Variables
2. Expectations and Independence
3. Bernoulli Processes and Sums of Independent Random Variables
4. Poisson Processes
5. Markov Chains
6. Limiting Behavior and Applications of Markov Chains
7. Potentials, Excessive Functions, and Optimal Stopping of Markov Chains
8. Markov Processes
9. Renewal Theory
10. Markov Renewal Theory
Appendix. Non-Negative Matrices
Answers to Selected Exercises
Index of Notations
Subject Index 

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