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A Weak Convergence Approach to the Theory of Large Deviations Book

A Weak Convergence Approach to the Theory of Large Deviations
A Weak Convergence Approach to the Theory of Large Deviations, This book presents a new and widely applicable method to the theory of large deviations. This approach allows large deviation problems, which are nonlinear, to be reduced to problems that are essentially linear in nature (weak convergence improbability). , A Weak Convergence Approach to the Theory of Large Deviations has a rating of 3 stars
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A Weak Convergence Approach to the Theory of Large Deviations, This book presents a new and widely applicable method to the theory of large deviations. This approach allows large deviation problems, which are nonlinear, to be reduced to problems that are essentially linear in nature (weak convergence improbability). , A Weak Convergence Approach to the Theory of Large Deviations
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  • A Weak Convergence Approach to the Theory of Large Deviations
  • Written by author Paul Dupuis
  • Published by Wiley, John & Sons, Incorporated, February 1997
  • This book presents a new and widely applicable method to the theory of large deviations. This approach allows large deviation problems, which are nonlinear, to be reduced to problems that are essentially linear in nature (weak convergence improbability).
  • Applies the well-developed tools of the theory of weak convergence of probability measures to large deviation analysis—a consistent new approach The theory of large deviations, one of the most dynamic topics in probability today, studies rar
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1Formulation of Large Deviation Theory in Terms of the Laplace Principle1
2First Example: Sanov's Theorem48
3Second Example: Mogulskii's Theorem65
4Representation Formulas for Other Stochastic Processes92
5Compactness and Limit Properties for the Random Walk Model127
6Laplace Principle for the Random Walk Model with Continuous Statistics149
7Laplace Principle for the Random Walk Model with Discontinuous Statistics216
8Laplace Principle for the Empirical Measures of a Markov Chain275
9Extensions of the Laplace Principle for the Empirical Measures of a Markov Chain320
10Laplace Principle for Continuous-Time Markov Processes with Continuous Statistics350
App. ABackground Material371
App. BDeriving the Representation Formulas via Measure Theory400
App. CProofs of a Number of Results405
App. DConvex Functions431
App. EProof of Theorem 5.3.5 When Condition 5.4.1 Replaces Condition 5.3.1449
Bibliography458
Notation Index463
Author Index467
Subject Index469


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A Weak Convergence Approach to the Theory of Large Deviations, This book presents a new and widely applicable method to the theory of large deviations. This approach allows large deviation problems, which are nonlinear, to be reduced to problems that are essentially linear in nature (weak convergence improbability). , A Weak Convergence Approach to the Theory of Large Deviations

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A Weak Convergence Approach to the Theory of Large Deviations, This book presents a new and widely applicable method to the theory of large deviations. This approach allows large deviation problems, which are nonlinear, to be reduced to problems that are essentially linear in nature (weak convergence improbability). , A Weak Convergence Approach to the Theory of Large Deviations

A Weak Convergence Approach to the Theory of Large Deviations

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A Weak Convergence Approach to the Theory of Large Deviations, This book presents a new and widely applicable method to the theory of large deviations. This approach allows large deviation problems, which are nonlinear, to be reduced to problems that are essentially linear in nature (weak convergence improbability). , A Weak Convergence Approach to the Theory of Large Deviations

A Weak Convergence Approach to the Theory of Large Deviations

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