Based on a highly popular, well-established course taught by the authors, Stochastic Processes: An Introduction, Second Edition discusses the modeling and analysis of random experiments using the theory of probability. It focuses on the way in which the results or outcomes of experiments vary and evolve over time.
The text begins with a review of relevant fundamental probability. It then covers several basic gambling problems, random walks, and Markov chains. The authors go on to develop random processes continuous in time, including Poisson, birth and death processes, and general population models. While focusing on queues, they present an extended discussion on the analysis of associated stationary processes. The book also explores reliability and other random processes, such as branching processes, martingales, and a simple epidemic. The appendix contains key mathematical results for reference.
Ideal for a one-semester course on stochastic processes, this concise, updated textbook makes the material accessible to students by avoiding specialized applications and instead highlighting simple applications and examples. The associated website contains Mathematica® and R programs that offer flexibility in creating graphs and performing computations.
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Peter W. Jones is a professor and Pro Vice Chancellor for Research and Enterprise at Keele University in Staffordshire, UK.
Peter Smith is a Professor Emeritus in the School of Computing and Mathematics at Keele University in Staffordshire, UK.
... a clear, easily understandable and rather short overview on stochastic processes. The different topics are motivated very well, there are many graphs and 50―theoretical and practical―examples. ... the book is written very carefully ... for beginners, one could not imagine a better book.
―Dominik Wied, Statistical Papers (2011) 52
... a good resource as a textbook or as a reference to complement other literature, especially with the examples and problems provided.
―Biometrics, 67, September 2011
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