The goal of this book is to provide a rigorous foundation for the theory and practice of subsampling. The asymptotic consistency of subsampling distribution estimation is shown under extremely weak conditions, including cases where the bootstrap fails. Consistent estimation of the sampling distribution of a statistic allows for the construction of asymptotically valid inferential procedures, such as confidence intervals and hypothesis tests. The crux of the method relies on recomputing a statistic over appropriate subsamples of the data, and using these recomputed values to build up a sampling distribution.
Readers are assumed to have a background roughly equivalent to a first-year graduate course in theoretical statistics. A large number of examples should make the book of interest to graduate students, researchers, and practitioners alike.
"The book is one of the most comprehensive texts in the subsampling realm and provides a solid background for researchers working in the related areas of statistics."
V.V. Fedorov in "Short Book Reviews," Vol. 21/1, April 2001
Series: Springer Series in Statistics
Number Of Pages: 348
Published: 13th August 1999
Publisher: Springer-Verlag New York Inc.
Country of Publication: US
Dimensions (cm): 24.33 x 16.1
Weight (kg): 0.59