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Stopping Times and Directed Processes: Encyclopedia of Mathematics and its Applications, cartea 47

Autor G. A. Edgar, Louis Sucheston
en Limba Engleză Paperback – 10 mar 2010
The notion of 'stopping times' is a useful one in probability theory; it can be applied to both classical problems and fresh ones. This book presents this technique in the context of the directed set, stochastic processes indexed by directed sets, and many applications in probability, analysis and ergodic theory. Martingales and related processes are considered from several points of view. The book opens with a discussion of pointwise and stochastic convergence of processes, with concise proofs arising from the method of stochastic convergence. Later, the rewording of Vitali covering conditions in terms of stopping times clarifies connections with the theory of stochastic processes. Solutions are presented here for nearly all the open problems in the Krickeberg convergence theory for martingales and submartingales indexed by directed set. Another theme of the book is the unification of martingale and ergodic theorems.
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Specificații

ISBN-13: 9780521135085
ISBN-10: 0521135087
Pagini: 444
Dimensiuni: 156 x 234 x 23 mm
Greutate: 0.62 kg
Editura: Cambridge University Press
Colecția Cambridge University Press
Seria Encyclopedia of Mathematics and its Applications

Locul publicării:New York, United States

Cuprins

Introduction; 1. Stopping times; 2. Infinite measure and Orlicz spaces; 3. Inequalities; 4. Directed index set; 5. Banach-valued random variables; 6. Martingales; 7. Derivation; 8. Pointwise ergodic theorems; 9. Multiparameter processes; References; Index.

Recenzii

"...will be extremely valuable to anybody doing research on directed processes. It is highly original. Most of the material has been published only in research journals so far....will be an indispensable and rich source of information previously scattered throughout many journals." U. Krengel, Mathematical Reviews

Descriere

A unified treatment of the theory of 'stopping times' for probability theorists and statisticians.