A Weak Convergence Approach To The Theory Of Large Deviations


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A Weak Convergence Approach to the Theory of Large Deviations


A Weak Convergence Approach to the Theory of Large Deviations

Author: Paul Dupuis

language: en

Publisher: John Wiley & Sons

Release Date: 2011-09-09


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Applies the well-developed tools of the theory of weak convergenceof probability measures to large deviation analysis--a consistentnew approach The theory of large deviations, one of the most dynamic topics inprobability today, studies rare events in stochastic systems. Thenonlinear nature of the theory contributes both to its richness anddifficulty. This innovative text demonstrates how to employ thewell-established linear techniques of weak convergence theory toprove large deviation results. Beginning with a step-by-stepdevelopment of the approach, the book skillfully guides readersthrough models of increasing complexity covering a wide variety ofrandom variable-level and process-level problems. Representationformulas for large deviation-type expectations are a key tool andare developed systematically for discrete-time problems. Accessible to anyone who has a knowledge of measure theory andmeasure-theoretic probability, A Weak Convergence Approach to theTheory of Large Deviations is important reading for both studentsand researchers.

A Weak Convergence Approach to the Theory of Large Deviations


A Weak Convergence Approach to the Theory of Large Deviations

Author: Paul Dupuis

language: en

Publisher: John Wiley & Sons

Release Date: 1997-02-27


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Applies the well-developed tools of the theory of weak convergenceof probability measures to large deviation analysis--a consistentnew approach The theory of large deviations, one of the most dynamic topics inprobability today, studies rare events in stochastic systems. Thenonlinear nature of the theory contributes both to its richness anddifficulty. This innovative text demonstrates how to employ thewell-established linear techniques of weak convergence theory toprove large deviation results. Beginning with a step-by-stepdevelopment of the approach, the book skillfully guides readersthrough models of increasing complexity covering a wide variety ofrandom variable-level and process-level problems. Representationformulas for large deviation-type expectations are a key tool andare developed systematically for discrete-time problems. Accessible to anyone who has a knowledge of measure theory andmeasure-theoretic probability, A Weak Convergence Approach to theTheory of Large Deviations is important reading for both studentsand researchers.

Large Deviations for Stochastic Processes


Large Deviations for Stochastic Processes

Author: Jin Feng

language: en

Publisher:

Release Date: 2014-05-21


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This work is devoted to the results on large deviations for a class of stochastic processes. Following an introduction and overview, the material is presented in three parts.