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On the Bootstrap and Empirical Processes for Dependent Sequences

  • Chapter
Empirical Process Techniques for Dependent Data

Abstract

The goal of this paper is to describe recent advances in empirical processes theory and several bootstraps for dependent data. We will address both theory and applications. The first three sections deal with the heuristics, motivation, statement of results and applications. The last section is devoted to mathematical techniques behind the theory. Although some results presented here are new (bootstrap for Markov chains), this is not a research paper, and the presented proofs do not contain all the details.

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Authors and Affiliations

  1. Program in Applied and Computational Mathematics, Department of Mathematics, Princeton University, Fine Hall 213, NJ, 08648, USA

    Dragan Radulović

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  1. Dragan Radulović
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Editors and Affiliations

  1. Fakultät für Mathematik, Ruhr-Universität Bochum, 44780, Bochum, Germany

    Herold Dehling

  2. Laboratory of Actuarial Mathematics, University of Copenhagen, DK-2100, Copenhagen, Denmark

    Thomas Mikosch

  3. Department of Statistics and Operations Research, University of Copenhagen, DK-2100, Copenhagen, Denmark

    Michael Sørensen

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Radulović, D. (2002). On the Bootstrap and Empirical Processes for Dependent Sequences. In: Dehling, H., Mikosch, T., Sørensen, M. (eds) Empirical Process Techniques for Dependent Data. Birkhäuser, Boston, MA. https://doi.org/10.1007/978-1-4612-0099-4_13

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  • DOI: https://doi.org/10.1007/978-1-4612-0099-4_13

  • Publisher Name: Birkhäuser, Boston, MA

  • Print ISBN: 978-1-4612-6611-2

  • Online ISBN: 978-1-4612-0099-4

  • eBook Packages: Springer Book Archive

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