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The purpose of this book is to present results on the subject of weak convergence in function spaces to study invariance principles in statistical applications to dependent random variables, U-statistics, censor data analysis. Different techniques, formerly available only in a broad range of literature, are for the first time presented here in a self-contained fashion. Contents:Weak convergence of stochastic processesWeak convergence in metric spacesWeak convergence on C[0, 1] and D[0,∞)Central limit theorem for semi-martingales and applicationsCentral limit theorems for dependent random variablesEmpirical processBibliography

Limit theorems (Probability theory) --- Probabilities

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The general topic of this book is the ergodic behavior of Markov processes. A detailed introduction to methods for proving ergodicity and upper bounds for ergodic rates is presented in the first part of the book, with the focus put on weak ergodic rates, typical for Markov systems with complicated structure. The second part is devoted to the application of these methods to limit theorems for functionals of Markov processes. The book is aimed at a wide audience with a background in probability and measure theory. Some knowledge of stochastic processes and stochastic differential equations helps in a deeper understanding of specific examples. Contents　Part I: Ergodic Rates for Markov Chains and ProcessesMarkov Chains with Discrete State SpacesGeneral Markov Chains: Ergodicity in Total VariationMarkovProcesseswithContinuousTimeWeak Ergodic Rates Part II: Limit TheoremsThe Law of Large Numbers and the Central Limit TheoremFunctional Limit Theorems

Markov processes --- Analysis, Markov --- Chains, Markov --- Markoff processes --- Markov analysis --- Markov chains --- Markov models --- Models, Markov --- Processes, Markov --- Stochastic processes --- Markov processes. --- ergodic rates. --- ergodicity. --- limit theorems.

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The book provides a general introduction to the theory of large deviations and a wide overview of the metastable behaviour of stochastic dynamics. With only minimal prerequisites, the book covers all the main results and brings the reader to the most recent developments. Particular emphasis is given to the fundamental Freidlin-Wentzell results on small random perturbations of dynamical systems. Metastability is first described on physical grounds, following which more rigorous approaches to its description are developed. Many relevant examples are considered from the point of view of the so-called pathwise approach. The first part of the book develops the relevant tools including the theory of large deviations which are then used to provide a physically relevant dynamical description of metastability. Written to be accessible to graduate students, this book provides an excellent route into contemporary research.

Large deviations. --- Stability. --- Dynamics --- Mechanics --- Motion --- Vibration --- Benjamin-Feir instability --- Equilibrium --- Deviations, Large --- Limit theorems (Probability theory) --- Statistics --- Mathematical statistics --- Large deviations --- Stability

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The subject of this book lies on the boundary between probability theory and the theory of function spaces. Here Professor Braverman investigates independent random variables in rearrangement invariant (r.i.) spaces. The significant feature of r.i. spaces is that the norm of an element depends on its distribution only, and this property allows the results and methods associated with r.i. spaces to be applied to problems in probability theory. On the other hand, probabilistic methods can also prove useful in the study of r.i. spaces. In this book new techniques are used and a number of interesting results are given. Most of the results are due to the author but have never before been available in English. Here they are all presented together in a volume that will be essential reading for all serious researchers in this area.

Random variables. --- Rearrangement invariant spaces. --- Inequalities (Mathematics) --- Processes, Infinite --- Invariant spaces, Rearrangement --- Spaces, Rearrangement invariant --- Function spaces --- Chance variables --- Stochastic variables --- Probabilities --- Variables (Mathematics) --- Probability --- Random variables --- Rearrangement invariant spaces --- Variables aléatoires --- Sous espaces invariants --- 519.214 --- 519.214 Limit theorems --- Limit theorems

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Limit theorems and asymptotic results form a central topic in probability theory and mathematical statistics. New and non-classical limit theorems have been discovered for processes in random environments, especially in connection with random matrix theory and free probability. These questions and the techniques for answering them combine asymptotic enumerative combinatorics, particle systems and approximation theory, and are important for new approaches in geometric and metric number theory as well. Thus, the contributions in this book include a wide range of applications with surprising connections ranging from longest common subsequences for words, permutation groups, random matrices and free probability to entropy problems and metric number theory. The book is the product of  a conference that took place in August 2011 in Bielefeld, Germany to celebrate the 60th birthday of Friedrich Götze, a noted expert in this field.

Limit theorems (Probability theory) -- Congresses. --- Mathematics --- Physical Sciences & Mathematics --- Mathematical Statistics --- Probabilities --- Number theory. --- Mathematical models. --- Number study --- Numbers, Theory of --- Probability --- Statistical inference --- Mathematics. --- Functional analysis. --- Probabilities. --- Probability Theory and Stochastic Processes. --- Functional Analysis. --- Number Theory. --- Algebra --- Combinations --- Chance --- Least squares --- Mathematical statistics --- Risk --- Distribution (Probability theory. --- Functional calculus --- Calculus of variations --- Functional equations --- Integral equations --- Distribution functions --- Frequency distribution --- Characteristic functions --- Limit theorems (Probability theory) --- Gotze, Friedrich.