Resampling Methods for Dependent Data

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ISBN-13:
9780387009285
Einband:
HC runder Rücken kaschiert
Erscheinungsdatum:
07.08.2003
Seiten:
396
Autor:
S. N. Lahiri
Gewicht:
758 g
Format:
241x160x27 mm
Serie:
Springer Series in Statistics
Sprache:
Englisch
Beschreibung:

By giving a detailed account of bootstrap methods and their properties for dependent data, this book provides illustrative numerical examples throughout. The book fills a gap in the literature covering research on re-sampling methods for dependent data that has witnessed vigorous growth over the last two decades but remains scattered in various statistics and econometrics journals. It can be used as a graduate level text and also as a research monograph for statisticians and econometricians.
1 Scope of Resampling Methods for Dependent Data.- 2 Bootstrap Methods.- 3 Properties of Block Bootstrap Methods for the Sample Mean.- 4 Extensions and Examples.- 5 Comparison of Block Bootstrap Methods.- 6 Second-Order Properties.- 7 Empirical Choice of the Block Size.- 8 Model-Based Bootstrap.- 9 Frequency Domain Bootstrap.- 10 Long-Range Dependence.- 11 Bootstrapping Heavy-Tailed Data and Extremes.- 12 Resampling Methods for Spatial Data.- A.- B.- References.- Author Index.

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