The Jackknife and Bootstrap (Hardcover, 1st ed. 1995. Corr. 2nd printing 1996)

The Jackknife and bootstrap are the most popular data-resampling methods used in statistical analysis. This book provides a systematic introduction to the theory of the jackknife, bootstrap and other resampling methods that have been developed in the last twenty years. It aims to provide a guide to using these methods which will enable applied statisticians to feel comfortable in applying them to data in their own research. The authors have included examples of applying these methods in various applications in both the independent and identically distributed (iid) case and in more complicated cases with non-iid data sets. Readers are assumed to have a reasonable knowledge of mathematical statistics and so this will be made suitable reading for graduate students, researchers and practitioners seeking a wide-ranging survey of this important area of statistical theory and application.

General

Imprint:	Springer-Verlag New York
Country of origin:	United States
Series:	Springer Series in Statistics
Release date:	September 1996
First published:	1995
Authors:	Jun Shao • Dongsheng Tu
Dimensions:	235 x 155 x 33mm (L x W x T)
Format:	Hardcover
Pages:	517
Edition:	1st ed. 1995. Corr. 2nd printing 1996
ISBN-13:	978-0-387-94515-6
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics Books > Science & Mathematics > Mathematics > Applied mathematics > General
LSN:	0-387-94515-6
Barcode:	9780387945156

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