Title Details: | |
An introduction to Large Deviations Theory |
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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.
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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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