Titlebook: Resampling Methods for Dependent Data; S. N. Lahiri Book 2003 Springer-Verlag New York 2003 Bootstrapping.Resampling.Ringe.STATISTICA.perm

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Bootstrap Methods,7, we describe various block bootstrap methods. A description of the subsampling method is given in Section 2.8. Bootstrap methods based on the discrete Fourier transform of the data are described in Section 2.9, while those based on the method of sieves are presented in Section 2.10.

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Extensions and Examples,l in Section 4.3. Section 4.4 gives results on the bootstrapped empirical process, and establishes consistency of bootstrap estimators for certain differentiable statistical functionals. Section 4.5 contains three numerical examples, illustrating the theoretical results of Sections 4.2–4.4.

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Properties of Block Bootstrap Methods for the Sample Mean,tion function estimations for the sample mean. The SB method uses a random block length and hence, requires a somewhat different treatment. We study consistency properties of the SB method for the sample mean in Section 3.3.

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Scope of Resampling Methods for Dependent Data,ocesses and point out situations where different types of bootstrap methods can be applied effectively, and also look at situations where these methods run into problems and point out possible remedies, if there is one known.

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Empirical Choice of the Block Size,of Hall, Horowitz and Jing (1995). A second method based on the Jackknife-After-Bootstrap (JAB) method is presented in Section 7.4. Numerical results on finite sample performance of these optimal block length selection rules are also given in the respective sections.

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978-1-4419-1848-2Springer-Verlag New York 2003