Here is a practical and mathematically rigorous introduction to the field of asymptotic statistics. In addition to most of the standard topics of an asymptotics course—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, one of the book's unifying themes that mainly entails the local approximation of the classical i.i.d. set up with smooth parameters by location experiments involving a single, normally distributed observation.
Product Details
ISBN-13: 9780521784504
Media Type: Paperback
Publisher: Cambridge University Press
Publication Date: 06-19-2000
Pages: 462
Product Dimensions: 6.81(w) x 9.09(h) x 1.06(d)
Series: Cambridge Series in Statistical and Probabilistic Mathematic #3
Table of Contents