Skip to main content Accessibility help
×
  1. Home
  2. Browse subjects
  3. Statistics and Probability
  4. Probability theory and stochastic processes
  5. Content listing

Refine search

Refine search

Access:
Content type:
Publication date:
Apply   From and To filters
Subject: Show more
Journals Show more
Publishers: Show more
Societies Show more
Series: Show more
Collections: Show more

Actions for selected content:

Select all | Deselect all
  • View selected items
  • Export citations
  • Download PDF (zip)
  • Save to Kindle
  • Save to Dropbox
  • Save to Google Drive

Save Search

You can save your searches here and later view and run them again in "My saved searches".

Please provide a title, maximum of 40 characters.
Cancel
×

3023 results in Probability theory and stochastic processes

Page 92 of 152

  • Preface

  • Geoffrey Grimmett, University of Cambridge
  • Book:
    Probability on Graphs
    Published online:
    05 June 2012
    Print publication:
    24 June 2010, pp ix-xii

  • Summary

    Within the menagerie of objects studied in contemporary probability theory, there are a number of related animals that have attracted great interest amongst probabilists and physicists in recent years. The inspiration for many of these objects comes from physics, but the mathematical subject has taken on a life of its own, and many beautiful constructions have emerged. The overall target of these notes is to identify some of these topics, and to develop their basic theory at a level suitable for mathematics graduates.

    If the two principal characters in these notes are random walk and percolation, they are only part of the rich theory of uniform spanning trees, self-avoiding walks, random networks, models for ferromagnetism and the spread of disease, and motion in random environments. This is an area that has attracted many fine scientists, by virtue, perhaps, of its special mixture of modelling and problem-solving. There remain many open problems. It is the experience of the author that these may be explained successfully to a graduate audience open to inspiration and provocation.

    The material described here may be used for personal study, and as the bases of lecture courses of between 24 and 48 hours duration. Little is assumed about the mathematical background of the audience beyond some basic probability theory, but students should be willing to get their hands dirty if they are to profit.

Uniform Central Limit Theorems
  • R. M. Dudley
  • Published online:
    20 May 2010
    Print publication:
    28 July 1999
  • This book shows how the central limit theorem for independent, identically distributed random variables with values in general, multidimensional spaces, holds uniformly over some large classes of functions. The author, an acknowledged expert, gives a thorough treatment of the subject, including several topics not found in any previous book, such as the Fernique-Talagrand majorizing measure theorem for Gaussian processes, an extended treatment of Vapnik-Chervonenkis combinatorics, the Ossiander L2 bracketing central limit theorem, the Giné-Zinn bootstrap central limit theorem in probability, the Bronstein theorem on approximation of convex sets, and the Shor theorem on rates of convergence over lower layers. Other results of Talagrand and others are surveyed without proofs in separate sections. Problems are included at the end of each chapter so the book can be used as an advanced text. The book will interest mathematicians working in probability, mathematical statisticians and computer scientists working in computer learning theory.

Asymptotic Analysis of Random Walks
  • Heavy-Tailed Distributions
  • A. A. Borovkov, K. A. Borovkov
  • Published online:
    07 May 2010
    Print publication:
    12 June 2008
  • This book focuses on the asymptotic behaviour of the probabilities of large deviations of the trajectories of random walks with 'heavy-tailed' (in particular, regularly varying, sub- and semiexponential) jump distributions. Large deviation probabilities are of great interest in numerous applied areas, typical examples being ruin probabilities in risk theory, error probabilities in mathematical statistics, and buffer-overflow probabilities in queueing theory. The classical large deviation theory, developed for distributions decaying exponentially fast (or even faster) at infinity, mostly uses analytical methods. If the fast decay condition fails, which is the case in many important applied problems, then direct probabilistic methods usually prove to be efficient. This monograph presents a unified and systematic exposition of the large deviation theory for heavy-tailed random walks. Most of the results presented in the book are appearing in a monograph for the first time. Many of them were obtained by the authors.

Stochastic Analysis
  • Proceedings of the Durham Symposium on Stochastic Analysis, 1990
  • Edited by M. T. Barlow, N. H. Bingham
  • Published online:
    31 March 2010
    Print publication:
    25 October 1991
  • Durham Symposia traditionally constitute an excellent survey of recent developments in many areas of mathematics. The Symposium on stochastic analysis, which took place at the University of Durham in July 1990, was no exception. This volume is edited by the organizers of the Symposium, and contains papers contributed by leading specialists in diverse areas of probability theory and stochastic processes. Of particular note are the papers by David Aldous, Harry Kesten and Alain-Sol Sznitman, all of which are based upon short courses of invited lectures. Researchers into the varied facets of stochastic analysis will find that these proceedings are an essential purchase.

Page 92 of 152