Resampling Methods for Dependent Data

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.

Inhalt

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.