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Title Details:
An introduction to Large Deviations Theory
Authors: Loulakis, Michail
Stamatakis, Marios-Georgios
Subject: MATHEMATICS AND COMPUTER SCIENCE > MATHEMATICS > PROBABILITY THEORY AND STOCHASTIC PROCESSES > LIMIT THEOREMS
MATHEMATICS AND COMPUTER SCIENCE > MATHEMATICS > PROBABILITY THEORY AND STOCHASTIC PROCESSES > STOCHASTIC PROCESSES
MATHEMATICS AND COMPUTER SCIENCE > MATHEMATICS > PROBABILITY THEORY AND STOCHASTIC PROCESSES > STOCHASTIC ANALYSIS
MATHEMATICS AND COMPUTER SCIENCE > MATHEMATICS > PROBABILITY THEORY AND STOCHASTIC PROCESSES > MARKOV PROCESSES
NATURAL SCIENCES AND AGRICULTURAL SCIENCES > PHYSICS > GENERAL PHYSICS > STATISTICAL PHYSICS AND THERMODYNAMICS
MATHEMATICS AND COMPUTER SCIENCE > MATHEMATICS > FUNCTIONAL ANALYSIS > TOPOLOGICAL LINEAR SPACES AND RELATED STRUCTURES
MATHEMATICS AND COMPUTER SCIENCE > MATHEMATICS > CONVEX AND DISCRETE GEOMETRY > GENERAL CONVEXITY
Keywords:
Large deviations
Cramér's Theorem
Rate function
Rare events
Varadhan's Lemma
Relative entropy
Contraction principle
Gibbs principle
Sanov's theorem
Legendre transform
Donsker-Varadhan Theorem
Freidlin-Wentzel Theory
Schilder's Theorem
Description:
Abstract:
It is common in Probability Theory that the distribution of random variables concentrates around a typical value, in the limit of some parameter. A classic example is the law of large numbers, by which the average of independent, identically distributed random variables concentrates around their common mean, as their number tends to infinity. Whenever we can infer an asymptotically typical behaviour, it is natural to ask about typical fluctuations, as well as the probability to observe a large deviation from the typical behaviour. This question, that is the asymptotic analysis of rare events and its consequences, is the central question of the Theory of Large Deviations. More than an area of Probability Theory, the Theory of Large Deviations is a set of principles, ideas and tools that can be useful in very diverse areas of Probability, and, in this sense it intersects most areas of Probability Theory. The aim of this book is to introduce the reader to the Theory of Large Deviations, as well as to showcase its many applications, which even extend to other scientific disciplines.
Linguistic Editors: Lampropoulou, Anastasia
Technical Editors: Stamatakis, Marios-Georgios
Type: Postgraduate textbook
Creation Date: 23-08-2024
Item Details:
ISBN 978-618-228-279-3
License: Attribution - NonCommercial - ShareAlike 4.0 International (CC BY-NC-SA 4.0)
DOI http://dx.doi.org/10.57713/kallipos-1026
Handle http://hdl.handle.net/11419/13844
Bibliographic Reference: Loulakis, M., & Stamatakis, M. (2024). An introduction to Large Deviations Theory [Postgraduate textbook]. Kallipos, Open Academic Editions. https://dx.doi.org/10.57713/kallipos-1026
Language: Greek
Consists of:
1. Introduction
2. Cramér's Theorem for random vectors with full exponential moments
3. General Principles of the Theory of Large Deviations, part 1
4. Sanov's Theorem and Gibbs principle in finite spaces
5. An application to Statistical Physics: The Curie-Weiss model
6. Generalisation of Cramér's Theorem and large deviations without independence
7. General Principles of the Theory of Large Deviations, part 2
8. Sanov's Theorem and Gibbs principle
9. Large deviations for Markov chains
10. Appendix A: Elements of convex analysis
11. Appendix B: Topological measure theory
12. Appendix C: Variational characterisation of integral functionals
Number of pages 275
Publication Origin: Kallipos, Open Academic Editions
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