Rabi Bhattacharya

Random Dynamical Systems (eBook, PDF)

Theory and Applications

• Format: PDF

Produktbeschreibung

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.

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Produktdetails

• Verlag: Cambridge University Press
• Erscheinungstermin: 8. Januar 2007
• Englisch
• ISBN-13: 9780511271106
• Artikelnr.: 38197661

Autorenporträt

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).

Inhaltsangabe

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.