An Introduction to Markov Processes

Daniel W. Stroock - Collection Graduate Texts in Mathematics

172 pages, parution le 02/06/2005

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Résumé

This book provides a rigorous but elementary introduction to the theory of Markov Processes on a countable state space. It should be accessible to students with a solid undergraduate background in mathematics, including students from engineering, economics, physics, and biology. Topics covered are: Doeblin's theory, general ergodic properties, and continuous time processes. A whole chapter is devoted to reversible processes and the use of their associated Dirichlet forms to estimate the rate of convergence to equilibrium.

Written for:

Advanced undergraduates with strong mathematics preparation and graduate students looking for a non-measure-theoretic, but rigorous, introduction to Markov processes

L'auteur - Daniel W. Stroock

Daniel W. Stroock is a Simons Professor of Mathematics at the Massachusetts Institute of Technology and the author of several books, including A Concise Introduction to the Theory of Integration and Probability Theory, an Analytic View.

Sommaire

Preface
Random Walks a Good Place to Begin
Doeblin's Theory for Markov Chains
More about the Ergodic Theory of Markov Chains
Markov Processes in Continuous Time
Reversible Markov Processes
Some Mild Measure Theory
Notation
References
Index

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Caractéristiques techniques

	PAPIER
Éditeur(s)	Springer
Auteur(s)	Daniel W. Stroock
Collection	Graduate Texts in Mathematics
Parution	02/06/2005
Nb. de pages	172
Format	15,5 x 23,5
Couverture	Broché
Poids	292g
Intérieur	Noir et Blanc
EAN13	9783540234517