This treatment provides an exposition of discrete time dynamic processes evolving over an infinite horizon. Chapter 1 reviews some mathematical results from the theory of deterministic dynamical systems, with particular emphasis on applications to economics. The theory of irreducible Markov processes, especially Markov chains, is surveyed in Chapter 2. Equilibrium and long run stability of a dynamical system in which the law of motion is subject to random perturbations is the central theme of Chapters 3-5. A unified account of relatively recent results, exploiting splitting and contractions, that have found applications in many contexts is presented in detail. Chapter 6 explains how a random dynamical system may emerge from a class of dynamic programming problems. With examples and exercises, readers are guided from basic theory to the frontier of applied mathematical research.
- Ideal for undergraduate and graduate courses on dynamic economics, Markov processes, Stochastic processes/probability
- Authors are internationally renowned for their work in this field
- Full of examples with many solutions, drawn from both applied mathematics and econometrics/statistics
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Reviews & endorsements
'This reviewer has all the arguments to recommend the book strongly not only to institutional libraries but also to anybody who is studying, teaching or using stochastic models. With its contents and style of presentation this attractive book will be very useful to postgraduate students in several areas, among them mathematics, statistics or probability, economics, biology or engineering.' Journal of the Royal Statistical Society

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11th Dec 2018 by Shuage
The Random Dynamical Systems: Theory and Applications is a fundamental and good book.

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Product details
- Date Published: March 2007
- format: Paperback
- isbn: 9780521532723
- length: 480 pages
- dimensions: 229 x 154 x 24 mm
- weight: 0.626kg
- availability: In stock
Table of Contents
1. Dynamical systems
2. Markov processes
3. Random dynamical systems
4. Random dynamical systems: special structures
5. Invariant distributions: estimations and computation
6. Discounted dynamic programming under uncertainty
7. Appendix.
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Authors
Rabi Bhattacharya, University of Arizona
Rabi Bhattacharya is Professor of Mathematics at the University of Arizona. He has also taught at the University of California at Berkeley and Indiana University. Professor Bhattacharya has held visiting research professorships at the University of Goetttingen, the University of Bielefeld, and the Indian Statistical Institute. He is a recipient of a Guggenheim Fellowship and an Alexander Von Humboldt Forschungspreis. He is a Fellow of the Institute of Mathematical Statistics and has served on the editorial boards of a number of international journals, including the Annals of Probability, Annals of Applied Probability, Journal of Multivariate Analysis, and Statistica Sinica. He has co-authored Normal Approximations and Asymptotic Expansions (with R. Ranga Rao), Stochastic Processes with Applications (with E. C. Waymire), and Asymptotic Statistics (with M. Denker).
Mukul Majumdar, Cornell University, New York
Mukul Majumdar is H. T. and R. I. Warshow Professor of Economics at Cornell University. He has also taught at Stanford University and the London School of Economics. Professor Majumdar is a Fellow of the Econometric Society and has been a Guggenheim Fellow, a Ford Rotating Research at the University of California, Berkeley, an Erskine Fellow at the University of Canterbury, an Oskar Morgenstern Visiting Professor at New York University, a Lecturer at the College de France and an Overseas Fellow at Churchill College, Cambridge University. Professor Majumdar has served on the editorial boards of many leading journals, including The Review of Economic Studies, Journal of Economic Theory, Journal of Mathematical Economics, and Economic Theory, and edited the collection Organizations with Incomplete Information (Cambridge University Press, 1998).