UID:
almahu_9948233799002882
Format:
1 online resource (xv, 443 pages) :
,
digital, PDF file(s).
ISBN:
9780511802256 (ebook)
Series Statement:
Cambridge series on statistical and probabilistic mathematics ; 3
Content:
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 research in asymptotic statistics.
Note:
Title from publisher's bibliographic system (viewed on 08 Oct 2015).
Additional Edition:
Print version: ISBN 9780521496032
Language:
English
URL:
https://doi.org/10.1017/CBO9780511802256
