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The bootstrap of the mean for strong mixing sequences under minimal conditions

Author

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  • Radulovic, Dragan

Abstract

It is shown that if a strongly mixing sequence satisfies the Central Limit Theorem, then it also satisfies the Moving Blocks Bootstrap Central Limit Theorem in probability, even with bootstrapped norming. Regarding bootstrap in probability, this is the best possible result along the line of Künsch (1989) and Liu and Singh (1992).

Suggested Citation

  • Radulovic, Dragan, 1996. "The bootstrap of the mean for strong mixing sequences under minimal conditions," Statistics & Probability Letters, Elsevier, vol. 28(1), pages 65-72, June.
    • Handle: RePEc:eee:stapro:v:28:y:1996:i:1:p:65-72
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    References listed on IDEAS

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    1. Peligrad, Magda, 1992. "On the central limit theorem for weakly dependent sequences with a decomposed strong mixing coefficient," Stochastic Processes and their Applications, Elsevier, vol. 42(2), pages 181-193, September.
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    Cited by:

    1. Cousido-Rocha, Marta & de Uña-Álvarez, Jacobo & Hart, Jeffrey D., 2019. "A two-sample test for the equality of univariate marginal distributions for high-dimensional data," Journal of Multivariate Analysis, Elsevier, vol. 174(C).
    2. Blaskowitz, Oliver & Herwartz, Helmut, 2014. "Testing the value of directional forecasts in the presence of serial correlation," International Journal of Forecasting, Elsevier, vol. 30(1), pages 30-42.
    3. Oliver Blaskowitz & Helmut Herwartz, 2008. "Testing directional forecast value in the presence of serial correlation," SFB 649 Discussion Papers SFB649DP2008-073, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    4. Efstathios Paparoditis & Dimitris Politis, 2000. "Large-sample inference in the general AR(1) model," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 9(2), pages 487-509, December.

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