Weak Convergence of Measures

Weak Convergence of Measures
Author: Patrick Billingsley
Publisher: SIAM
Total Pages: 37
Release: 1971-01-01
Genre: Mathematics
ISBN: 9781611970623

A treatment of the convergence of probability measures from the foundations to applications in limit theory for dependent random variables. Mapping theorems are proved via Skorokhod's representation theorem; Prokhorov's theorem is proved by construction of a content. The limit theorems at the conclusion are proved under a new set of conditions that apply fairly broadly, but at the same time make possible relatively simple proofs.

Convergence of Probability Measures

Convergence of Probability Measures
Author: Patrick Billingsley
Publisher: John Wiley & Sons
Total Pages: 253
Release: 2013-06-25
Genre: Mathematics
ISBN: 111862596X

A new look at weak-convergence methods in metric spaces-from a master of probability theory In this new edition, Patrick Billingsley updates his classic work Convergence of Probability Measures to reflect developments of the past thirty years. Widely known for his straightforward approach and reader-friendly style, Dr. Billingsley presents a clear, precise, up-to-date account of probability limit theory in metric spaces. He incorporates many examples and applications that illustrate the power and utility of this theory in a range of disciplines-from analysis and number theory to statistics, engineering, economics, and population biology. With an emphasis on the simplicity of the mathematics and smooth transitions between topics, the Second Edition boasts major revisions of the sections on dependent random variables as well as new sections on relative measure, on lacunary trigonometric series, and on the Poisson-Dirichlet distribution as a description of the long cycles in permutations and the large divisors of integers. Assuming only standard measure-theoretic probability and metric-space topology, Convergence of Probability Measures provides statisticians and mathematicians with basic tools of probability theory as well as a springboard to the "industrial-strength" literature available today.

A Weak Convergence Approach to the Theory of Large Deviations

A Weak Convergence Approach to the Theory of Large Deviations
Author: Paul Dupuis
Publisher: John Wiley & Sons
Total Pages: 506
Release: 2011-09-09
Genre: Mathematics
ISBN: 1118165896

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.

The Dual of L∞(X,L,λ), Finitely Additive Measures and Weak Convergence

The Dual of L∞(X,L,λ), Finitely Additive Measures and Weak Convergence
Author: John Toland
Publisher: Springer Nature
Total Pages: 104
Release: 2020-01-03
Genre: Mathematics
ISBN: 303034732X

In measure theory, a familiar representation theorem due to F. Riesz identifies the dual space Lp(X,L,λ)* with Lq(X,L,λ), where 1/p+1/q=1, as long as 1 ≤ p∞. However, iL/isub∞/sub(X,L,λ)* cannot be similarly described, and is instead represented as a class of finitely additive measures./ppThis book provides a reasonably elementary account of the representation theory of iL/isub∞/sub(X,L,λ)*, examining pathologies and paradoxes, and uncovering some surprising consequences. For instance, a necessary and sufficient condition for a bounded sequence in iL/isub∞/sub(X,L,λ) to be weakly convergent, applicable in the one-point compactification of X, is given./ppWith a clear summary of prerequisites, and illustrated by examples including iL/isub∞/sub(bR/bsupn/sup) and the sequence space il/isub∞/sub, this book makes possibly unfamiliar material, some of which may be new, accessible to students and researchers in the mathematical sciences.

Weak Convergence Methods and Singularly Perturbed Stochastic Control and Filtering Problems

Weak Convergence Methods and Singularly Perturbed Stochastic Control and Filtering Problems
Author: Harold Kushner
Publisher: Springer Science & Business Media
Total Pages: 245
Release: 2012-12-06
Genre: Mathematics
ISBN: 146124482X

The book deals with several closely related topics concerning approxima tions and perturbations of random processes and their applications to some important and fascinating classes of problems in the analysis and design of stochastic control systems and nonlinear filters. The basic mathematical methods which are used and developed are those of the theory of weak con vergence. The techniques are quite powerful for getting weak convergence or functional limit theorems for broad classes of problems and many of the techniques are new. The original need for some of the techniques which are developed here arose in connection with our study of the particular applica tions in this book, and related problems of approximation in control theory, but it will be clear that they have numerous applications elsewhere in weak convergence and process approximation theory. The book is a continuation of the author's long term interest in problems of the approximation of stochastic processes and its applications to problems arising in control and communication theory and related areas. In fact, the techniques used here can be fruitfully applied to many other areas. The basic random processes of interest can be described by solutions to either (multiple time scale) Ito differential equations driven by wide band or state dependent wide band noise or which are singularly perturbed. They might be controlled or not, and their state values might be fully observable or not (e. g. , as in the nonlinear filtering problem).

Weak Convergence of Measures

Weak Convergence of Measures
Author: Vladimir I. Bogachev
Publisher: American Mathematical Society
Total Pages: 301
Release: 2024-07-29
Genre: Mathematics
ISBN: 147047798X

This book provides a thorough exposition of the main concepts and results related to various types of convergence of measures arising in measure theory, probability theory, functional analysis, partial differential equations, mathematical physics, and other theoretical and applied fields. Particular attention is given to weak convergence of measures. The principal material is oriented toward a broad circle of readers dealing with convergence in distribution of random variables and weak convergence of measures. The book contains the necessary background from measure theory and functional analysis. Large complementary sections aimed at researchers present the most important recent achievements. More than 100 exercises (ranging from easy introductory exercises to rather difficult problems for experienced readers) are given with hints, solutions, or references. Historic and bibliographic comments are included. The target readership includes mathematicians and physicists whose research is related to probability theory, mathematical statistics, functional analysis, and mathematical physics.

Convergence of Stochastic Processes

Convergence of Stochastic Processes
Author: D. Pollard
Publisher: David Pollard
Total Pages: 223
Release: 1984-10-08
Genre: Mathematics
ISBN: 0387909907

Functionals on stochastic processes; Uniform convergence of empirical measures; Convergence in distribution in euclidean spaces; Convergence in distribution in metric spaces; The uniform metric on space of cadlag functions; The skorohod metric on D [0, oo); Central limit teorems; Martingales.

Non-Life Insurance Mathematics

Non-Life Insurance Mathematics
Author: Thomas Mikosch
Publisher: Springer Science & Business Media
Total Pages: 435
Release: 2009-04-21
Genre: Mathematics
ISBN: 3540882332

"Offers a mathematical introduction to non-life insurance and, at the same time, to a multitude of applied stochastic processes. It gives detailed discussions of the fundamental models for claim sizes, claim arrivals, the total claim amount, and their probabilistic properties....The reader gets to know how the underlying probabilistic structures allow one to determine premiums in a portfolio or in an individual policy." --Zentralblatt für Didaktik der Mathematik

Analysis and Approximation of Rare Events

Analysis and Approximation of Rare Events
Author: Amarjit Budhiraja
Publisher: Springer
Total Pages: 577
Release: 2019-08-10
Genre: Mathematics
ISBN: 1493995790

This book presents broadly applicable methods for the large deviation and moderate deviation analysis of discrete and continuous time stochastic systems. A feature of the book is the systematic use of variational representations for quantities of interest such as normalized logarithms of probabilities and expected values. By characterizing a large deviation principle in terms of Laplace asymptotics, one converts the proof of large deviation limits into the convergence of variational representations. These features are illustrated though their application to a broad range of discrete and continuous time models, including stochastic partial differential equations, processes with discontinuous statistics, occupancy models, and many others. The tools used in the large deviation analysis also turn out to be useful in understanding Monte Carlo schemes for the numerical approximation of the same probabilities and expected values. This connection is illustrated through the design and analysis of importance sampling and splitting schemes for rare event estimation. The book assumes a solid background in weak convergence of probability measures and stochastic analysis, and is suitable for advanced graduate students, postdocs and researchers.