Asymptotic Statistics

ISBN-10: 0521784506
ISBN-13: 9780521784504
Edition: 2000
List price: $67.00 Buy it from $45.61
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Description: This book is an introduction to the field of asymptotic statistics. The treatment is both practical and mathematically rigorous. In addition to most of the standard topics of an asymptotics course, including likelihood inference, M-estimation, the  More...

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Book details

List price: $67.00
Copyright year: 2000
Publisher: Cambridge University Press
Publication date: 6/19/2000
Binding: Paperback
Pages: 462
Size: 6.75" wide x 9.50" long x 1.00" tall
Weight: 1.782
Language: English

This book is an introduction to the field of asymptotic statistics. The treatment is both practical and mathematically rigorous. In addition to most of the standard topics of an asymptotics course, including likelihood inference, M-estimation, the theory of asymptotic efficiency, U-statistics, and rank procedures, the book also presents recent research topics such as semiparametric models, the bootstrap, and empirical processes and their applications. The topics are organized from the central idea of approximation by limit experiments, which gives the book one of its unifying themes. This entails mainly the local approximation of the classical i.i.d. set up with smooth parameters by location experiments involving a single, normally distributed observation. Thus, even the standard subjects of asymptotic statistics are presented in a novel way. Suitable as a graduate or Master's level statistics text, this book will also give researchers an overview of the latest research in asymptotic statistics.

Introduction
Stochastic convergence
The delta-method
Moment estimators
M- and Z-estimators
Contiguity
Local asymptotic normality
Efficiency of estimators
Limits of experiments
Bayes procedures
Projections
U-statistics
Rank, sign, and permutation statistics
Relative efficiency of tests
Efficiency of tests
Likelihood ratio tests
Chi-square tests
Stochastic convergence in metric spaces
Empirical processes
The functional delta-method
Quantiles and order statistics
L-statistics
The bootstrap
Nonparametric density estimation
Semiparametric models

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