Since Efron's profound paper on the bootstrap, an enormous amount of effort has been spent on the development of bootstrap, jacknife, and other resampling methods. The primary goal of these computer-intensive methods has been to provide statistical tools that work in complex situations without imposing unrealistic or unverifiable assumptions about the data generating mechanism. This book sets out to lay some of the foundations for subsampling methodology and related methods.

Since Efron's profound paper on the bootstrap, an enormous amount of effort has been spent on the development of bootstrap, jacknife, and other resampling methods. The primary goal of these computer-intensive methods has been to provide statistical tools that work in complex situations without imposing unrealistic or unverifiable assumptions about the data generating mechanism. The primary goal of this book is to lay some of the foundation for subsampling methodology and related methods.

Front Matter Pages i-xv Front Matter Pages 1-1 Bootstrap Sampling Distributions Pages 3-38 Subsampling in the I.I.D. Case Pages 39-64 Subsampling for Stationary Time Series Pages 65-100 Subsampling for Nonstationary Time Series Pages 101-119 Subsampling for Random Fields Pages 120-137 Subsampling Marked Point Processes Pages 138-158 Confidence Sets for General Parameters Pages 159-170 Front Matter Pages 171-171 Subsampling with Unknown Convergence Rate Pages 173-187 Choice of the Block Size Pages 188-212 Extrapolation, Interpolation, and Higher-Order Accuracy Pages 213-252 Subsampling the Mean with Heavy Tails Pages 253-269 Subsampling the Autoregressive Parameter Pages 270-290 Subsampling Stock Returns Pages 291-314 Back Matter Pages 315-348