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Block length selection in the bootstrap for time series

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  • Buhlmann, Peter
  • Kunsch, Hans R.

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  • Buhlmann, Peter & Kunsch, Hans R., 1999. "Block length selection in the bootstrap for time series," Computational Statistics & Data Analysis, Elsevier, vol. 31(3), pages 295-310, September.
    • Handle: RePEc:eee:csdana:v:31:y:1999:i:3:p:295-310
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    References listed on IDEAS

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    1. Lahiri, Soumendra Nath, 1991. "Second order optimality of stationary bootstrap," Statistics & Probability Letters, Elsevier, vol. 11(4), pages 335-341, April.
    2. Politis, D. N. & Romano, J. P., 1993. "Nonparametric Resampling for Homogeneous Strong Mixing Random Fields," Journal of Multivariate Analysis, Elsevier, vol. 47(2), pages 301-328, November.
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    Cited by:

    1. Bücher, Axel & Ruppert, Martin, 2013. "Consistent testing for a constant copula under strong mixing based on the tapered block multiplier technique," Journal of Multivariate Analysis, Elsevier, vol. 116(C), pages 208-229.
    2. George Kapetanios & Fotis Papailias, 2011. "Block Bootstrap and Long Memory," Working Papers 679, Queen Mary University of London, School of Economics and Finance.
    3. Allen, Jason & Gregory, Allan W. & Shimotsu, Katsumi, 2011. "Empirical likelihood block bootstrapping," Journal of Econometrics, Elsevier, vol. 161(2), pages 110-121, April.
    4. Eduardo José Araújo Lima & Benjamin Miranda Tabak, 2008. "Exchange Rate Dynamics and the Relationship between the Random Walk Hypothesis and Official Interventions," Working Papers Series 173, Central Bank of Brazil, Research Department.
    5. Shao, Xiaofeng, 2011. "A bootstrap-assisted spectral test of white noise under unknown dependence," Journal of Econometrics, Elsevier, vol. 162(2), pages 213-224, June.
    6. Palm, Franz C. & Smeekes, Stephan & Urbain, Jean-Pierre, 2011. "Cross-sectional dependence robust block bootstrap panel unit root tests," Journal of Econometrics, Elsevier, vol. 163(1), pages 85-104, July.
    7. Gaißer, Sandra & Ruppert, Martin & Schmid, Friedrich, 2010. "A multivariate version of Hoeffding's Phi-Square," Journal of Multivariate Analysis, Elsevier, vol. 101(10), pages 2571-2586, November.
    8. George Kapetanios & Fotis Papailias, 2011. "Block Bootstrap and Long Memory," Working Papers 679, Queen Mary University of London, School of Economics and Finance.
    9. Bertail, Patrice & Clemencon, Stephan, 2008. "Approximate regenerative-block bootstrap for Markov chains," Computational Statistics & Data Analysis, Elsevier, vol. 52(5), pages 2739-2756, January.
    10. Cerqueti, Roy & Falbo, Paolo & Pelizzari, Cristian, 2017. "Relevant states and memory in Markov chain bootstrapping and simulation," European Journal of Operational Research, Elsevier, vol. 256(1), pages 163-177.
    11. Jalal, Amine & Rockinger, Michael, 2008. "Predicting tail-related risk measures: The consequences of using GARCH filters for non-GARCH data," Journal of Empirical Finance, Elsevier, vol. 15(5), pages 868-877, December.
    12. Wu, Edmond H.C. & Yu, Philip L.H. & Li, W.K., 2009. "A smoothed bootstrap test for independence based on mutual information," Computational Statistics & Data Analysis, Elsevier, vol. 53(7), pages 2524-2536, May.
    13. F. Giordano & M. La Rocca & C. Perna, 2011. "Properties of the neural network sieve bootstrap," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 23(3), pages 803-817.

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