David M. Goldsman, Georgia Institute of Technology
"Sean Meyn's earlier book with Tweedie is the bible for economists who use Markov models to do everything from formulating asset pricing models to constructing Bayesian posteriors for dynamic models. This book is a gold mine of useful new ideas. I predict that the ideas in chapter 11 alone will have a big impact on the way we think about computing rational expectations equilibria."
Thomas Sargent, New York University; Winner of the 2011 Nobel Prize in Economic Sciences
"The first comprehensive account of some major strands of research in modeling, approximation, stability analysis and optimization of stochastic networks, from a leader in the field...Notable among these are its coverage of deterministic fluid limits, controlled random walk models, approximation via workload relaxation, and implications of these to stability and optimization of networks. Several important special instances are worked out in detail. A valuable resource for both researchers and practitioners."
Vivek S. Borkar, Tata Institute of Fundamental Research
"...outstanding and it should become an indispensable aid to researchers and practitioners... All in all this is an excellent book useful primarily to researchers in the field."
Yannis A. Phillis, Mathematical Reviews
"The main goal of the book is to describe how simpler, more parsimonious descriptions of a complex network may be used to reach conclusions on the stability, control and design of the original network. The book does a superb job in bringing to light the whole gamut of issues, ranging from modeling and control to simulation, that must be considered... A particularly pleasing aspect of the book is how self-contained it is... This book will no doubt become an invaluable resource for graduate students, researchers and practitioners in this field."
Kavita Ramanan, Journal of the American Statistical Association