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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 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.
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All the information you need in one place! Each Study Brief is a summary of one specific subject; facts, figures, and explanations to help you learn faster.
List price: $67.00
Copyright year: 2000
Publisher: Cambridge University Press
Publication date: 6/19/2000
Size: 6.75" wide x 9.50" long x 1.00" tall
|M- and Z-estimators|
|Local asymptotic normality|
|Efficiency of estimators|
|Limits of experiments|
|Rank, sign, and permutation statistics|
|Relative efficiency of tests|
|Efficiency of tests|
|Likelihood ratio tests|
|Stochastic convergence in metric spaces|
|The functional delta-method|
|Quantiles and order statistics|
|Nonparametric density estimation|