A modern presentation of the 'Lyapunov function' method applied to near-critical stochastic systems, exemplified by non-homogeneous random walks.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Mikhail Menshikov is Professor in the Department of Mathematical Sciences at the University of Durham. His research interests include percolation theory, where Menshikov's theorem is a cornerstone of the subject. He has published extensively on the Lyapunov function method and its application, for example to queueing theory.
Inhaltsangabe
1. Introduction 2. Semimartingale approach and Markov chains 3. Lamperti's problem 4. Many-dimensional random walks 5. Heavy tails 6. Further applications 7. Markov chains in continuous time Glossary of named assumptions Bibliography Index.
1. Introduction 2. Semimartingale approach and Markov chains 3. Lamperti's problem 4. Many-dimensional random walks 5. Heavy tails 6. Further applications 7. Markov chains in continuous time Glossary of named assumptions Bibliography Index.
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