Subsampling is an important research area in nonparametric statistics, and is of interest to statisticians in many different areas.

Autorentext
Joseph P. Romano is Professor of Statistics at Stanford University. He is a recipient of a Presidential Young Investigator Award and a Fellow of the Institute of Mathematical Statistics.

Inhalt
I Basic Theory.- 1 Bootstrap Sampling Distributions.- 2 Subsampling in the I.I.D. Case.- 3 Subsampling for Stationary Time Series.- 4 Subsampling for Nonstationary Time Series.- 5 Subsampling for Random Fields.- 6 Subsampling Marked Point Processes.- 7 Confidence Sets for General Parameters.- II Extensions, Practical Issues, and Applications.- 8 Subsampling with Unknown Convergence Rate.- 9 Choice of the Block Size.- 10 Extrapolation, Interpolation, and Higher-Order Accuracy.- 11 Subsampling the Mean with Heavy Tails.- 12 Subsampling the Autoregressive Parameter.- 13 Subsampling Stock Returns.- Appendices.- A Some Results on Mixing.- B A General Central Limit Theorem.- References.- Index of Names.- Index of Subjects.