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High Dimensional Probability III

  • Conference proceedings
  • © 2003

Overview

Editors:
  1. Jørgen Hoffmann-Jørgensen

    1. Department of Mathematical Sciences, University of Aarhus, Arhus C, Denmark

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  2. Jon A. Wellner

    1. Department of Statistics, University of Washington, Seattle, USA

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  3. Michael B. Marcus

    1. Department of Mathematics, City College, New York, USA

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  • Rigorously refereed contributions originating from the 3rd international conference on High Dimensional Probability in Sandjberg, Denmark, June 2002

Part of the book series: Progress in Probability (PRPR, volume 55)

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Table of contents (20 papers)

  1. Front Matter

    Pages i-viii
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  2. Measures on General Spaces and Inequalities

    1. Front Matter

      Pages 1-1
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    2. Stochastic inequalities and perfect independence

      • J. Hoffmann-Jørgensen
      Pages 3-34

    3. Prokhorov—LeCam—Varadarajan’s Compactness Criteria for Vector Measures on Metric Spaces

      • Jun Kawabe
      Pages 35-42

    4. On Measures in Locally Convex Spaces

      • A. V. Uglanov
      Pages 43-54

  5. Local Times

    1. Front Matter

      Pages 175-175
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    2. Local Time-Space Calculus and Extensions of Itô’s Formula

      • Raouf Ghomrasni, Goran Peskir
      Pages 177-192

    3. Local Times on Curves and Surfaces

      • Michael B. Marcus
      Pages 193-202

  6. Large and Small Deviations

    1. Front Matter

      Pages 203-203
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    2. Large Deviations of Empirical Processes

      • Miguel A. Arcones
      Pages 205-223

    3. Small Deviation Estimates for Some Additive Processes

      • Xia Chen, Wenbo V. Li
      Pages 225-238
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Keywords

About this book

The title High Dimensional Probability is an attempt to describe the many trib­ utaries of research on Gaussian processes and probability in Banach spaces that started in the early 1970's. In each of these fields it is necessary to consider large classes of stochastic processes under minimal conditions. There are rewards in re­ search of this sort. One can often gain deep insights, even about familiar processes, by stripping away details that in hindsight turn out to be extraneous. Many of the problems that motivated researchers in the 1970's were solved. But the powerful new tools created for their solution, such as randomization, isoperimetry, concentration of measure, moment and exponential inequalities, chaining, series representations and decoupling turned out to be applicable to other important areas of probability. They led to significant advances in the study of empirical processes and other topics in theoretical statistics and to a new ap­ proach to the study of aspects of Levy processes and Markov processes in general. Papers on these topics as well as on the continuing study of Gaussian processes and probability in Banach are included in this volume.

Editors and Affiliations

  • Department of Mathematical Sciences, University of Aarhus, Arhus C, Denmark

    Jørgen Hoffmann-Jørgensen

  • Department of Statistics, University of Washington, Seattle, USA

    Jon A. Wellner

  • Department of Mathematics, City College, New York, USA

    Michael B. Marcus

Bibliographic Information

  • Book Title: High Dimensional Probability III

  • Editors: Jørgen Hoffmann-Jørgensen, Jon A. Wellner, Michael B. Marcus

  • Series Title: Progress in Probability

  • DOI: https://doi.org/10.1007/978-3-0348-8059-6

  • Publisher: Birkhäuser Basel

  • eBook Packages: Springer Book Archive

  • Copyright Information: Springer Science+Business Media New York 2003

  • Hardcover ISBN: 978-3-7643-2187-1Published: 27 November 2003

  • Softcover ISBN: 978-3-0348-9423-4Published: 23 October 2012

  • eBook ISBN: 978-3-0348-8059-6Published: 06 December 2012

  • Series ISSN: 1050-6977

  • Series E-ISSN: 2297-0428

  • Edition Number: 1

  • Number of Pages: VIII, 346

  • Topics: Probability Theory and Stochastic Processes, Measure and Integration, Statistics, general

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