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An urn-based Bayesian block bootstrap

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  • Pasquale Cirillo

  • Pietro Muliere

Abstract

Block bootstrap has been introduced in the literature for resampling dependent data, i.e. stationary processes. One of the main assumptions in block bootstrapping is that the blocks of observations are exchangeable, i.e. their joint distribution is immune to permutations. In this paper we propose a new Bayesian approach to block bootstrapping, starting from the construction of exchangeable blocks. Our sampling mechanism is based on a particular class of reinforced urn processes. Copyright Springer-Verlag 2013

Suggested Citation

  • Pasquale Cirillo & Pietro Muliere, 2013. "An urn-based Bayesian block bootstrap," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 76(1), pages 93-106, January.
    • Handle: RePEc:spr:metrik:v:76:y:2013:i:1:p:93-106
    DOI: 10.1007/s00184-011-0377-1
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    References listed on IDEAS

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    1. Pietro Muliere & Stephen Walker, 1998. "Extending the family of Bayesian bootstraps and exchangeable urn schemes," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 60(1), pages 175-182.
    2. Muliere, P. & Secchi, P. & Walker, S. G., 2000. "Urn schemes and reinforced random walks," Stochastic Processes and their Applications, Elsevier, vol. 88(1), pages 59-78, July.
    3. P. Muliere & P. Secchi, 1996. "Bayesian nonparametric predictive inference and bootstrap techniques," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 48(4), pages 663-673, December.
    4. Andrew Patton & Dimitris Politis & Halbert White, 2009. "Correction to “Automatic Block-Length Selection for the Dependent Bootstrap” by D. Politis and H. White," Econometric Reviews, Taylor & Francis Journals, vol. 28(4), pages 372-375.
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    Cited by:

    1. Pasquale Cirillo & Mauro Gallegati & Jürg Hüsler, 2012. "A Pólya Lattice Model To Study Leverage Dynamics And Contagious Financial Fragility," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 15(supp0), pages 1-26.
    2. Philippe Goulet Coulombe, 2024. "The macroeconomy as a random forest," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(3), pages 401-421, April.

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