Buch, Englisch, 448 Seiten, Format (B × H): 161 mm x 240 mm, Gewicht: 830 g
Buch, Englisch, 448 Seiten, Format (B × H): 161 mm x 240 mm, Gewicht: 830 g
ISBN: 978-0-471-53631-4
Verlag: Wiley
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.
Autoren/Hrsg.
Weitere Infos & Material
Partial table of contents:
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.




