Exploring the Limits of Bootstrap
Wiley Series in Probability and Statistics

1. Auflage April 1992
448 Seiten, Hardcover
Wiley & Sons Ltd
Explores the application of bootstrap to problems that place unusual demands on the method. The bootstrap method, introduced by Bradley Efron in 1973, is a nonparametric technique for inferring the distribution of a statistic derived from a sample. Most of the papers were presented at a special meeting sponsored by the Institute of Mathematical Statistics and the Interface Foundation in May, 1990.
GENERAL PRINCIPLES OF THE BOOTSTRAP.
On the Bootstrap of M-Estimators and Other Statistical Functionals(M. Arcones & E. Gine).
Bootstrapping Markov Chains (K. Athreya & C. Fuh).
Six Questions Raised by the Bootstrap (B. Efron).
Efficient Bootstrap Simulation (P. Hall).
Bootstrapping Signs (R. LePage).
Bootstrap Bandwidth Selection (J. Marron).
APPLICATIONS OF THE BOOTSTRAP.
A Generalized Bootstrap (E. Bedrick & J. Hill).
Bootstrapping Admissible Linear Model Selection Procedures (D.Brownstone).
A Hazard Process for Survival Analysis (J. Hsieh).
A Nonparametric Density Estimation Based Resampling Algorithm (M.Taylor & J. Thompson).
Nonparametric Rank Estimation Using Bootstrap Resampling andCanonical Correlation Analysis (X. Tu, et al.).
Index.