Provides a clear and concise explanation of stochastic theory with an emphasis on computation and examples. This practical graduate text develops theory at an understandable technical level and offers challenging examples to underscore theoretical principles. A special section at the end of each chapter offers additional examples and applications to reinforce the theory in the chapter exercises, and the self-contained chapter on measure theory can be used as a short course or integrated into a general stochastic processes class. The sample course outlines that illustrate the different types of courses that could be based on the text will be of particular interest to professors/instructors.
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A very broad coverage of the most applicable aspects of stochastic processes. The emphasis is on the most important classes of these processes from the viewpoint of theory as well as applications, namely, Markov processes. It is for graduate students, but will also be useful to professionals as a reference.
Rabi N. Bhattacharya is a Professor of Mathematics at the University of Arizona. He is an IMS Fellow, a member of the AMS, and a recipient of the Humboldt Prize and a Guggenheim Fellowship.
Edward C. Waymire is a Professor of Mathematics and Statistics at Oregon State University. He is a member of the AMS and SIAM,, a Fellow of the IMS, and past Editor in Chief for the Annals of Applied Probability.
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