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Approximate Regenerative-block Bootstrap for Markov Chains : Some Simulation Studies

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  • Patrice Bertail

    (Crest)

  • Stéphan Clémençon

    (Crest)

Abstract

: In Bertail & Clémençon (2005a) a novel methodology for bootstrappinggeneral Harris Markov chains has been proposed, which crucially exploits their renewalproperties (when eventually extended via the Nummelin splitting technique) and has theoreticalproperties that surpass other existing methods within the Markovian framework(bmoving block bootstrap, sieve bootstrap etc...). This paper is devoted to discuss practicalissues related to the implementation of this specific resampling method and to presentvarious simulations studies for investigating the performance of the latter and comparingit to other bootstrap resampling schemes standing as natural candidates in the Markovsetting.

Suggested Citation

  • Patrice Bertail & Stéphan Clémençon, 2006. "Approximate Regenerative-block Bootstrap for Markov Chains : Some Simulation Studies," Working Papers 2006-19, Center for Research in Economics and Statistics.
    • Handle: RePEc:crs:wpaper:2006-19
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    References listed on IDEAS

    as
    1. M. Rajarshi, 1990. "Bootstrap in Markov-sequences based on estimates of transition density," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 42(2), pages 253-268, June.
    2. J. Michael Harrison & Sidney I. Resnick, 1976. "The Stationary Distribution and First Exit Probabilities of a Storage Process with General Release Rule," Mathematics of Operations Research, INFORMS, vol. 1(4), pages 347-358, November.
    3. Dimitris Politis & Halbert White, 2004. "Automatic Block-Length Selection for the Dependent Bootstrap," Econometric Reviews, Taylor & Francis Journals, vol. 23(1), pages 53-70.
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