Limit Theorems of Probability Theory

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.


A History of the Central Limit Theorem

A History of the Central Limit Theorem

Author: Hans Fischer

Publisher: Springer Science & Business Media

Published: 2010-10-08

Total Pages: 415

ISBN-13: 0387878572

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This study discusses the history of the central limit theorem and related probabilistic limit theorems from about 1810 through 1950. In this context the book also describes the historical development of analytical probability theory and its tools, such as characteristic functions or moments. The central limit theorem was originally deduced by Laplace as a statement about approximations for the distributions of sums of independent random variables within the framework of classical probability, which focused upon specific problems and applications. Making this theorem an autonomous mathematical object was very important for the development of modern probability theory.


Probability

Probability

Author: Rick Durrett

Publisher: Cambridge University Press

Published: 2010-08-30

Total Pages:

ISBN-13: 113949113X

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This classic introduction to probability theory for beginning graduate students covers laws of large numbers, central limit theorems, random walks, martingales, Markov chains, ergodic theorems, and Brownian motion. It is a comprehensive treatment concentrating on the results that are the most useful for applications. Its philosophy is that the best way to learn probability is to see it in action, so there are 200 examples and 450 problems. The fourth edition begins with a short chapter on measure theory to orient readers new to the subject.


Limit Theorems in Probability, Statistics and Number Theory

Limit Theorems in Probability, Statistics and Number Theory

Author: Peter Eichelsbacher

Publisher: Springer Science & Business Media

Published: 2013-04-23

Total Pages: 317

ISBN-13: 3642360688

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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.


Mathematical Statistics and Limit Theorems

Mathematical Statistics and Limit Theorems

Author: Marc Hallin

Publisher: Springer

Published: 2015-04-07

Total Pages: 326

ISBN-13: 3319124420

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This Festschrift in honour of Paul Deheuvels’ 65th birthday compiles recent research results in the area between mathematical statistics and probability theory with a special emphasis on limit theorems. The book brings together contributions from invited international experts to provide an up-to-date survey of the field. Written in textbook style, this collection of original material addresses researchers, PhD and advanced Master students with a solid grasp of mathematical statistics and probability theory.


Heads or Tails

Heads or Tails

Author: Emmanuel Lesigne

Publisher: American Mathematical Soc.

Published: 2005

Total Pages: 162

ISBN-13: 0821837141

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Everyone knows some of the basics of probability, perhaps enough to play cards. Beyond the introductory ideas, there are many wonderful results that are unfamiliar to the layman, but which are well within our grasp to understand and appreciate. Some of the most remarkable results in probability are those that are related to limit theorems--statements about what happens when the trial is repeated many times. The most famous of these is the Law of Large Numbers, which mathematicians,engineers, economists, and many others use every day. In this book, Lesigne has made these limit theorems accessible by stating everything in terms of a game of tossing of a coin: heads or tails. In this way, the analysis becomes much clearer, helping establish the reader's intuition aboutprobability. Moreover, very little generality is lost, as many situations can be modelled from combinations of coin tosses. This book is suitable for anyone who would like to learn more about mathematical probability and has had a one-year undergraduate course in analysis.


Probability: The Classical Limit Theorems

Probability: The Classical Limit Theorems

Author: Henry McKean

Publisher: Cambridge University Press

Published: 2014-11-27

Total Pages: 487

ISBN-13: 1107053218

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A leading authority sheds light on a variety of interesting topics in which probability theory plays a key role.


Limit Theorems for Randomly Stopped Stochastic Processes

Limit Theorems for Randomly Stopped Stochastic Processes

Author: Dmitriĭ Sergeevich Silʹvestrov

Publisher: Springer Science & Business Media

Published: 2004

Total Pages: 426

ISBN-13: 9781852337773

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Limit theorems for stochastic processes are an important part of probability theory and mathematical statistics and one model that has attracted the attention of many researchers working in the area is that of limit theorems for randomly stopped stochastic processes.This volume is the first to present a state-of-the-art overview of this field, with many of the results published for the first time. It covers the general conditions as well as the basic applications of the theory, and it covers and demystifies the vast, and technically demanding, Russian literature in detail. A survey of the literature and an extended bibliography of works in the area are also provided.The coverage is thorough, streamlined and arranged according to difficulty for use as an upper-level text if required. It is an essential reference for theoretical and applied researchers in the fields of probability and statistics that will contribute to the continuing extensive studies in the area and remain relevant for years to come.


Information Theory and the Central Limit Theorem

Information Theory and the Central Limit Theorem

Author: Oliver Thomas Johnson

Publisher: World Scientific

Published: 2004

Total Pages: 224

ISBN-13: 1860944736

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This book provides a comprehensive description of a new method of proving the central limit theorem, through the use of apparently unrelated results from information theory. It gives a basic introduction to the concepts of entropy and Fisher information, and collects together standard results concerning their behaviour. It brings together results from a number of research papers as well as unpublished material, showing how the techniques can give a unified view of limit theorems.


Limit Theorems For Associated Random Fields And Related Systems

Limit Theorems For Associated Random Fields And Related Systems

Author: Alexander Bulinski

Publisher: World Scientific

Published: 2007-09-05

Total Pages: 447

ISBN-13: 9814474576

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This volume is devoted to the study of asymptotic properties of wide classes of stochastic systems arising in mathematical statistics, percolation theory, statistical physics and reliability theory. Attention is paid not only to positive and negative associations introduced in the pioneering papers by Harris, Lehmann, Esary, Proschan, Walkup, Fortuin, Kasteleyn and Ginibre, but also to new and more general dependence conditions. Naturally, this scope comprises families of independent real-valued random variables. A variety of important results and examples of Markov processes, random measures, stable distributions, Ising ferromagnets, interacting particle systems, stochastic differential equations, random graphs and other models are provided. For such random systems, it is worthwhile to establish principal limit theorems of the modern probability theory (central limit theorem for random fields, weak and strong invariance principles, functional law of the iterated logarithm etc.) and discuss their applications.There are 434 items in the bibliography.The book is self-contained, provides detailed proofs, for reader's convenience some auxiliary results are included in the Appendix (e.g. the classical Hoeffding lemma, basic electric current theory etc.).