This book develops systematically and rigorously, yet in an expository and lively manner, the evolution of general random processes and their large time properties such as transience, recurrence, and convergence to steady states. The emphasis is on the most important classes of these processes from the viewpoint of theory as well as applications, namely, Markov processes. The book features very broad coverage of the most applicable aspects of stochastic processes, including sufficient material for self-contained courses on random walks in one and multiple dimensions; Markov chains in discrete and continuous times, including birth-death processes; Brownian motion and diffusions; stochastic optimization; and stochastic differential equations. This book is for graduate students in mathematics, statistics, science and engineering, and it may also be used as a reference by professionals in diverse fields whose work involves the application of probability.
'This may be the best all-around treatment [of stochastic processes] for use by graduate students with varied backgrounds but with some mathematical ambitions.' William G. Faris, University of Arizona
'The book is remarkably comprehensive. The additional notes at the end of the chapters contain a fund of information.' Richard F. Gundy, Rutgers University
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