Large Deviations For Markov Chains
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Large Deviations For Additive Functionals Of Markov Chains
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Author : Alejandro D. de Acosta
language : en
Publisher: American Mathematical Soc.
Release Date : 2014-03-05
Large Deviations For Additive Functionals Of Markov Chains written by Alejandro D. de Acosta and has been published by American Mathematical Soc. this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-03-05 with Mathematics categories.
Large Deviations
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Author : Frank Hollander
language : en
Publisher: American Mathematical Soc.
Release Date : 2000
Large Deviations written by Frank Hollander and has been published by American Mathematical Soc. this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000 with Mathematics categories.
This volume offers an introduction to large deviations. It is divided into two parts: theory and applications. Basic large deviation theorems are presented for i.i.d. sequences, Markov sequences, and sequences with moderate dependence. The rate function is computed explicitly. The theory is explained without too much emphasis on technicalities. Also included is an outline of general definitions and theorems. The goal is to expose the unified theme that gives large deviation theory its overall structure, which can be made to work in many concrete cases. The section on applications focuses on recent work in statistical physics and random media. This book contains 60 exercises (with solutions) that should elucidate the content and engage the reader. Prerequisites for the book are a strong background in probability and analysis and some knowledge of statistical physics. It would make an excellent textbook for a special topics course in large deviations.
Large Deviations
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Author : Jean-Dominique Deuschel and Daniel W. Stroock
language : en
Publisher: American Mathematical Soc.
Release Date :
Large Deviations written by Jean-Dominique Deuschel and Daniel W. Stroock and has been published by American Mathematical Soc. this book supported file pdf, txt, epub, kindle and other format this book has been release on with Mathematics categories.
The second printing of a book first published in 1988. The first four chapters of the volume are based on lectures given by Stroock at MIT in 1987. They form an introduction to the basic ideas of the theory of large deviations and make a suitable package on which to base a semester-length course for advanced graduate students with a strong background in analysis and some probability theory. A large selection of exercises presents important material and many applications. The last two chapters present various non-uniform results and outline the analytic approach that allows one to test and compare techniques used in previous chapters.
A Weak Convergence Approach To The Theory Of Large Deviations
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Author : Paul Dupuis
language : en
Publisher: John Wiley & Sons
Release Date : 2011-09-09
A Weak Convergence Approach To The Theory Of Large Deviations written by Paul Dupuis and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-09-09 with Mathematics categories.
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 Markov Chains
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Author : Gilad Lerman
language : en
Publisher:
Release Date : 1995
Large Deviations For Markov Chains written by Gilad Lerman and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with Markov processes categories.
Large Deviations For Markov Chains
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Author : Alejandro D. de Acosta
language : en
Publisher:
Release Date : 2022-10-12
Large Deviations For Markov Chains written by Alejandro D. de Acosta and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-12 with Mathematics categories.
This book studies the large deviations for empirical measures and vector-valued additive functionals of Markov chains with general state space. Under suitable recurrence conditions, the ergodic theorem for additive functionals of a Markov chain asserts the almost sure convergence of the averages of a real or vector-valued function of the chain to the mean of the function with respect to the invariant distribution. In the case of empirical measures, the ergodic theorem states the almost sure convergence in a suitable sense to the invariant distribution. The large deviation theorems provide precise asymptotic estimates at logarithmic level of the probabilities of deviating from the preponderant behavior asserted by the ergodic theorems.
A Course On Large Deviations With An Introduction To Gibbs Measures
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Author : Firas Rassoul-Agha
language : en
Publisher: American Mathematical Soc.
Release Date : 2015-03-12
A Course On Large Deviations With An Introduction To Gibbs Measures written by Firas Rassoul-Agha and has been published by American Mathematical Soc. this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-03-12 with Mathematics categories.
This is an introductory course on the methods of computing asymptotics of probabilities of rare events: the theory of large deviations. The book combines large deviation theory with basic statistical mechanics, namely Gibbs measures with their variational characterization and the phase transition of the Ising model, in a text intended for a one semester or quarter course. The book begins with a straightforward approach to the key ideas and results of large deviation theory in the context of independent identically distributed random variables. This includes Cramér's theorem, relative entropy, Sanov's theorem, process level large deviations, convex duality, and change of measure arguments. Dependence is introduced through the interactions potentials of equilibrium statistical mechanics. The phase transition of the Ising model is proved in two different ways: first in the classical way with the Peierls argument, Dobrushin's uniqueness condition, and correlation inequalities and then a second time through the percolation approach. Beyond the large deviations of independent variables and Gibbs measures, later parts of the book treat large deviations of Markov chains, the Gärtner-Ellis theorem, and a large deviation theorem of Baxter and Jain that is then applied to a nonstationary process and a random walk in a dynamical random environment. The book has been used with students from mathematics, statistics, engineering, and the sciences and has been written for a broad audience with advanced technical training. Appendixes review basic material from analysis and probability theory and also prove some of the technical results used in the text.
Large Deviations For Stochastic Processes
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Author : Jin Feng
language : en
Publisher:
Release Date : 2014-05-21
Large Deviations For Stochastic Processes written by Jin Feng and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-21 with MATHEMATICS categories.
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.
Large Deviations For Additive Functionals Of Markov Chains
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Author : Alejandro D. de Acosta
language : en
Publisher:
Release Date : 2014-10-03
Large Deviations For Additive Functionals Of Markov Chains written by Alejandro D. de Acosta and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-10-03 with MATHEMATICS categories.
For a Markov chain {X?} with general state space S and f: S?R ?, the large deviation principle for {n ?1 ? =1 f(X?)} is proved under a condition on the chain which is weaker than uniform recurrence but stronger than geometric recurrence and an integrability condition on f, for a broad class of initial distributions. This result is extended to the case when f takes values in a separable Banach space. Assuming only geometric ergodicity and under a non-degeneracy condition, a local large deviation result is proved for bounded f. A central analytical tool is the transform kernel, whose required properties, including new results, are established. The rate function in the large deviation results is expressed in terms of the convergence parameter of the transform kernel.
Large Deviations And Applications
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Author : S. R. S. Varadhan
language : en
Publisher: SIAM
Release Date : 1984-01-01
Large Deviations And Applications written by S. R. S. Varadhan and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 1984-01-01 with Mathematics categories.
Many situations exist in which solutions to problems are represented as function space integrals. Such representations can be used to study the qualitative properties of the solutions and to evaluate them numerically using Monte Carlo methods. The emphasis in this book is on the behavior of solutions in special situations when certain parameters get large or small.