Large Deviations and Idempotent Probability

Large Deviations and Idempotent Probability
Author: Anatolii Puhalskii
Publisher: CRC Press
Total Pages: 515
Release: 2001-05-07
Genre: Business & Economics
ISBN: 1420035800

In the view of many probabilists, author Anatolii Puhalskii's research results stand among the most significant achievements in the modern theory of large deviations. In fact, his work marked a turning point in the depth of our understanding of the connections between the large deviation principle (LDP) and well-known methods for establishing weak

Large Deviations for Stochastic Processes

Large Deviations for Stochastic Processes
Author: Jin Feng
Publisher: American Mathematical Soc.
Total Pages: 426
Release: 2015-02-03
Genre: Mathematics
ISBN: 1470418703

The book 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. Part 1 gives necessary and sufficient conditions for exponential tightness that are analogous to conditions for tightness in the theory of weak convergence. Part 2 focuses on Markov processes in metric spaces. For a sequence of such processes, convergence of Fleming's logarithmically transformed nonlinear semigroups is shown to imply the large deviation principle in a manner analogous to the use of convergence of linear semigroups in weak convergence. Viscosity solution methods provide applicable conditions for the necessary convergence. Part 3 discusses methods for verifying the comparison principle for viscosity solutions and applies the general theory to obtain a variety of new and known results on large deviations for Markov processes. In examples concerning infinite dimensional state spaces, new comparison principles are derived for a class of Hamilton-Jacobi equations in Hilbert spaces and in spaces of probability measures.

Analytical and Computational Methods in Probability Theory

Analytical and Computational Methods in Probability Theory
Author: Vladimir V. Rykov
Publisher: Springer
Total Pages: 551
Release: 2017-12-21
Genre: Computers
ISBN: 3319715046

This book constitutes the refereed proceedings of the First International Conference on Analytical and Computational Methods in Probability Theory and its Applications, ACMPT 2017, held in Moscow, Russia, in October 2017. The 42 full papers presented were carefully reviewed and selected from 173 submissions. The conference program consisted of four main themes associated with significant contributions made by A.D.Soloviev. These are: Analytical methods in probability theory, Computational methods in probability theory, Asymptotical methods in probability theory, the history of mathematics.

Feynman-Kac Formulae

Feynman-Kac Formulae
Author: Pierre Del Moral
Publisher: Springer Science & Business Media
Total Pages: 567
Release: 2012-12-06
Genre: Mathematics
ISBN: 1468493930

This text takes readers in a clear and progressive format from simple to recent and advanced topics in pure and applied probability such as contraction and annealed properties of non-linear semi-groups, functional entropy inequalities, empirical process convergence, increasing propagations of chaos, central limit, and Berry Esseen type theorems as well as large deviation principles for strong topologies on path-distribution spaces. Topics also include a body of powerful branching and interacting particle methods.

Stochastic Differential Equations

Stochastic Differential Equations
Author: Peter H. Baxendale
Publisher: World Scientific
Total Pages: 416
Release: 2007
Genre: Mathematics
ISBN: 9812770631

This volume consists of 15 articles written by experts in stochastic analysis. The first paper in the volume, Stochastic Evolution Equations by N V Krylov and B L Rozovskii, was originally published in Russian in 1979. After more than a quarter-century, this paper remains a standard reference in the field of stochastic partial differential equations (SPDEs) and continues to attract the attention of mathematicians of all generations. Together with a short but thorough introduction to SPDEs, it presents a number of optimal, and essentially unimprovable, results about solvability for a large class of both linear and non-linear equations. The other papers in this volume were specially written for the occasion of Prof RozovskiiOCOs 60th birthday. They tackle a wide range of topics in the theory and applications of stochastic differential equations, both ordinary and with partial derivatives."

Idempotent Mathematics and Mathematical Physics

Idempotent Mathematics and Mathematical Physics
Author: Grigoriĭ Lazarevich Litvinov
Publisher: American Mathematical Soc.
Total Pages: 378
Release: 2005
Genre: Mathematics
ISBN: 0821835386

Idempotent mathematics is a rapidly developing new branch of the mathematical sciences that is closely related to mathematical physics. The existing literature on the subject is vast and includes numerous books and journal papers. A workshop was organized at the Erwin Schrodinger Institute for Mathematical Physics (Vienna) to give a snapshot of modern idempotent mathematics. This volume contains articles stemming from that event. Also included is an introductory paper by G. Litvinov and additional invited contributions. The resulting volume presents a comprehensive overview of the state of the art. It is suitable for graduate students and researchers interested in idempotent mathematics and tropical mathematics.

Asymptotic Analysis of Random Walks

Asymptotic Analysis of Random Walks
Author: A. A. Borovkov
Publisher: Cambridge University Press
Total Pages: 437
Release: 2020-10-29
Genre: Mathematics
ISBN: 1108901204

This is a companion book to Asymptotic Analysis of Random Walks: Heavy-Tailed Distributions by A.A. Borovkov and K.A. Borovkov. Its self-contained systematic exposition provides a highly useful resource for academic researchers and professionals interested in applications of probability in statistics, ruin theory, and queuing theory. The large deviation principle for random walks was first established by the author in 1967, under the restrictive condition that the distribution tails decay faster than exponentially. (A close assertion was proved by S.R.S. Varadhan in 1966, but only in a rather special case.) Since then, the principle has always been treated in the literature only under this condition. Recently, the author jointly with A.A. Mogul'skii removed this restriction, finding a natural metric for which the large deviation principle for random walks holds without any conditions. This new version is presented in the book, as well as a new approach to studying large deviations in boundary crossing problems. Many results presented in the book, obtained by the author himself or jointly with co-authors, are appearing in a monograph for the first time.

From Stochastic Calculus to Mathematical Finance

From Stochastic Calculus to Mathematical Finance
Author: Yu. Kabanov
Publisher: Springer Science & Business Media
Total Pages: 659
Release: 2007-04-03
Genre: Mathematics
ISBN: 3540307885

Dedicated to the Russian mathematician Albert Shiryaev on his 70th birthday, this is a collection of papers written by his former students, co-authors and colleagues. The book represents the modern state of art of a quickly maturing theory and will be an essential source and reading for researchers in this area. Diversity of topics and comprehensive style of the papers make the book attractive for PhD students and young researchers.