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Analysis and Approximation of Rare Events

Representations and Weak Convergence Methods
BuchGebunden
574 Seiten
Englisch
Springererschienen am11.08.20191st ed. 2019
This book presents broadly applicable methods for the large deviation and moderate deviation analysis of discrete and continuous time stochastic systems. By characterizing a large deviation principle in terms of Laplace asymptotics, one converts the proof of large deviation limits into the convergence of variational representations.mehr
Verfügbare Formate
BuchGebunden
EUR149,79
BuchKartoniert, Paperback
EUR149,79
E-BookPDF1 - PDF WatermarkE-Book
EUR139,09

Produkt

KlappentextThis book presents broadly applicable methods for the large deviation and moderate deviation analysis of discrete and continuous time stochastic systems. By characterizing a large deviation principle in terms of Laplace asymptotics, one converts the proof of large deviation limits into the convergence of variational representations.
Details
ISBN/GTIN978-1-4939-9577-6
ProduktartBuch
EinbandartGebunden
Verlag
Erscheinungsjahr2019
Erscheinungsdatum11.08.2019
Auflage1st ed. 2019
ReiheProbability Theory and Stochastic Modelling
Seiten574 Seiten
SpracheEnglisch
Gewicht1044 g
IllustrationenXIX, 574 p. 14 illus., 1 illus. in color.
Artikel-Nr.46190574

Inhalt/Kritik

Inhaltsverzeichnis
Preliminaries and elementary examples.- Discrete time processes.- Continuous time processes.- Monte Carlo approximation.âmehr
Kritik
"The book is very well organized and the structure of each chapter is helpful: notation, assumptions, statements, examples, proofs and comments are clearly separated. ... this makes the book a good reference for researchers interested in rare event analysis and approximation." ( Charles-Edouard Bréhier, Mathematical Reviews, August, 2020)
"The current book requires a solid background in weak convergence of probability measures and stochastic analysis, and it is intended for advanced graduate students, post-doctoral fellows and researchers working in this area." (Anatoliy Swishchuk, zbMATH 1427.60003, 2020)mehr

Autor

Amarjit Budhiraja is a Professor of Statistics and Operations Research at the University of North Carolina at Chapel Hill. He is a Fellow of the IMS. His research interests include stochastic analysis, the theory of large deviations, stochastic networks and stochastic nonlinear filtering.
Paul Dupuis is the IBM Professor of Applied Mathematics at Brown University and a Fellow of the AMS, SIAM and IMS. His research interests include stochastic control, the theory of large deviations and numerical methods.
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Budhiraja, Amarjit