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Book Categories |
1 | Formulation of Large Deviation Theory in Terms of the Laplace Principle | 1 |
2 | First Example: Sanov's Theorem | 48 |
3 | Second Example: Mogulskii's Theorem | 65 |
4 | Representation Formulas for Other Stochastic Processes | 92 |
5 | Compactness and Limit Properties for the Random Walk Model | 127 |
6 | Laplace Principle for the Random Walk Model with Continuous Statistics | 149 |
7 | Laplace Principle for the Random Walk Model with Discontinuous Statistics | 216 |
8 | Laplace Principle for the Empirical Measures of a Markov Chain | 275 |
9 | Extensions of the Laplace Principle for the Empirical Measures of a Markov Chain | 320 |
10 | Laplace Principle for Continuous-Time Markov Processes with Continuous Statistics | 350 |
App. A | Background Material | 371 |
App. B | Deriving the Representation Formulas via Measure Theory | 400 |
App. C | Proofs of a Number of Results | 405 |
App. D | Convex Functions | 431 |
App. E | Proof of Theorem 5.3.5 When Condition 5.4.1 Replaces Condition 5.3.1 | 449 |
Bibliography | 458 | |
Notation Index | 463 | |
Author Index | 467 | |
Subject Index | 469 |
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Add 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 to the inventory that you are selling on WonderClubX
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Add 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 to your collection on WonderClub |