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The blockwise bootstrap for general empirical processes of stationary sequences

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  • Bühlmann, Peter

Abstract

We apply the blockwise bootstrap for stationary observations, proposed by Künsch (1989), to empirical processes indexed by function classes which satisfy some bracketing conditions. We prove a bootstrap central limit theorem for empirical processes of stationary [beta]-mixing variables, which holds almost surely. This is done under a moment condition for the envelope function of and by assuming an exponential decay of the mixing coefficients. By using exponential inequalities we apply a chaining technique.

Suggested Citation

  • Bühlmann, Peter, 1995. "The blockwise bootstrap for general empirical processes of stationary sequences," Stochastic Processes and their Applications, Elsevier, vol. 58(2), pages 247-265, August.
    • Handle: RePEc:eee:spapps:v:58:y:1995:i:2:p:247-265
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    Cited by:

    1. Berkowitz, J. & Birgean, I. & Kilian, L., 1999. "On the Finite-Sample Accuracy of Nonparametric Resampling Algorithms for Economic Time Series," Papers 99-01, Michigan - Center for Research on Economic & Social Theory.
    2. Otsu, Taisuke & Seo, Myung Hwan & Whang, Yoon-Jae, 2012. "Testing for non-nested conditional moment restrictions using unconditional empirical likelihood," Journal of Econometrics, Elsevier, vol. 167(2), pages 370-382.
    3. Corradi, Valentina & Swanson, Norman R., 2005. "Bootstrap specification tests for diffusion processes," Journal of Econometrics, Elsevier, vol. 124(1), pages 117-148, January.
    4. Corradi, Valentina & Swanson, Norman R., 2006. "Bootstrap conditional distribution tests in the presence of dynamic misspecification," Journal of Econometrics, Elsevier, vol. 133(2), pages 779-806, August.

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