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Limit Theorems for Large Deviations

Author: L. Saulis

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 241

ISBN-13: 9401135304

"Et moi ... - si j'avait su comment en revenir. One service mathematics has rendered the je n'y serais poin t aile.' human race. It has put common sense back Jules Verne where it belongs, on the topmost shelf next to the dusty canister labelled 'discarded non- The series is divergent; therefore we may be sense'. able to do something with it. Eric T. Bell O.H ea viside Mathematics is a tool for thought. A highly necessary tool in a world where both feedback and non Iinearities abound. Similarly, all kinds of parts of mathematics serve as tools for other parts and for other sciences. Applying a simple rewriting rule to the quote on the right above one finds such statements as: 'One service. topology has rendered mathematical physics .. .':: 'One service logic has rendered com puter science .. .'; 'One service category theory has rendered mathematics .. .'. All arguably true. And all statements obtainable this way form part of the raison d 'e1:re of this series

Refined Large Deviation Limit Theorems

Author: Vladimir Vinogradov

Publisher: CRC Press

Published: 2023-06-14

Total Pages: 228

ISBN-13: 100094834X

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This is a developing area of modern probability theory, which has applications in many areas. This volume is devoted to the systematic study of results on large deviations in situations where Cramér's condition on the finiteness of exponential moments may not be satisfied

Limit Theorems on Large Deviations for Markov Stochastic Processes

Author: A.D. Wentzell

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 192

ISBN-13: 9400918526

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In recent decades a new branch of probability theory has been developing intensively, namely, limit theorems for stochastic processes. As compared to classical limit theorems for sums of independent random variables, the generalizations are going here in two directions simultaneously. First, instead of sums of independent variables one considers stochastic processes belonging to certain broad classes. Secondly, instead of the distribution of a single sum - the distribution of the value of a stochastic process at one (time) point - or the joint distribution of the values of a process at a finite number of points, one considers distributions in an infinite-dimensional function space. For stochastic processes constructed, starting from sums of independent random variables, this is the same as considering the joint distribution of an unboundedly increasing number of sums.

Limit Theorems of Probability Theory

Author: Yu.V. Prokhorov

Publisher: Springer Science & Business Media

Published: 2013-03-14

Total Pages: 280

ISBN-13: 3662041723

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A collection of research level surveys on certain topics in probability theory by a well-known group of researchers. The book will be of interest to graduate students and researchers.

Universal Theory For Strong Limit Theorems Of Probability

Author: Andrei N Frolov

Publisher: World Scientific

Published: 2019-10-10

Total Pages: 204

ISBN-13: 9811212848

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This is the first book which the universal approach to strong laws of probability is discussed in. The universal theories are described for three important objects of probability theory: sums of independent random variables, processes with independent increments and renewal processes. Further generalizations are mentioned. Besides strong laws, large deviations are of independent interest. The case of infinite variations is considered as well. Readers can examine appropriate techniques and methods. Optimality of conditions is discussed.

Advances in Probability Theory

Author: Aleksandr Alekseevich Borovkov

Publisher:

Published: 1984

Total Pages: 400

ISBN-13:

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Some Limit Theorems in Statistics

Author: R. R. Bahadur

Publisher: SIAM

Published: 1971-01-01

Total Pages: 48

ISBN-13: 9781611970630

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A discussion of some topics in the theory of large deviations such as moment-generating functions and Chernoff's theorem, and of aspects of estimation and testing in large samples, such as exact slopes of test statistics.

Large Deviations

Author: Frank Hollander

Publisher: American Mathematical Soc.

Published: 2000

Total Pages: 164

ISBN-13: 9780821844359

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Offers an introduction to large deviations. This book is divided into two parts: theory and applications. It presents basic large deviation theorems for i i d sequences, Markov sequences, and sequences with moderate dependence. It also includes an outline of general definitions and theorems.

Mod-φ Convergence

Author: Valentin Féray

Publisher: Springer

Published: 2016-12-06

Total Pages: 152

ISBN-13: 3319468227

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The canonical way to establish the central limit theorem for i.i.d. random variables is to use characteristic functions and Lévy’s continuity theorem. This monograph focuses on this characteristic function approach and presents a renormalization theory called mod-φ convergence. This type of convergence is a relatively new concept with many deep ramifications, and has not previously been published in a single accessible volume. The authors construct an extremely flexible framework using this concept in order to study limit theorems and large deviations for a number of probabilistic models related to classical probability, combinatorics, non-commutative random variables, as well as geometric and number-theoretical objects. Intended for researchers in probability theory, the text is carefully well-written and well-structured, containing a great amount of detail and interesting examples.

Local Limit Theorems for Inhomogeneous Markov Chains

Author: Dmitry Dolgopyat

Publisher: Springer Nature

Published: 2023-07-31

Total Pages: 348

ISBN-13: 3031326016

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This book extends the local central limit theorem to Markov chains whose state spaces and transition probabilities are allowed to change in time. Such chains are used to model Markovian systems depending on external time-dependent parameters. The book develops a new general theory of local limit theorems for additive functionals of Markov chains, in the regimes of local, moderate, and large deviations, and provides nearly optimal conditions for the classical expansions, as well as asymptotic corrections when these conditions fail. Applications include local limit theorems for independent but not identically distributed random variables, Markov chains in random environments, and time-dependent perturbations of homogeneous Markov chains. The inclusion of appendices with background material, numerous examples, and an account of the historical background of the subject make this self-contained book accessible to graduate students. It will also be useful for researchers in probability and ergodic theory who are interested in asymptotic behaviors, Markov chains in random environments, random dynamical systems and non-stationary systems.