Product Description

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

• Amazon Sales Rank: #327699 in Books
• Published on: 2000-06-19
• Original language: English
• Number of items: 1
• Binding: Paperback
• 460 pages

Review
'The book is extremely well written and clear ... it is comprehensive and has an abundant supply of worked examples ... anyone who is genuinely interested in learning about some of the recent developments in asymptotic statistics and their potential applications should have a copy of this book.' Biometrics

'I recommend this book to every advanced Master's student, Ph.D. student or researcher in mathematical statistics.' Kwantitatieve methoden

Customer Reviews

Excellent textbook on asymptotics in statistics
This book covers asymptotics at a level suitable for graduate students in statistics and other disciplines such as economics. It does not really treat time-series issues, but apart from that its coverage is very impressive. It covers M-estimators, efficiency, quantile estimators, semiparametrics, and much more. The writing is remarkably lucid; proofs are succinct but very readable. One feature I particularly liked was a very readable introduction to empirical process theory, which would be a good place to start before tackling the van der Vaart and Wellner's more advanced book.

Just read and enjoy.
An excellent book for graduate level. Many interesting material (like U-statistics and a flavor of nonparametric methods) exposed in a solid and precise way.

Asymptotic Statistics
Great book for an applied or a theoretical statistician. Particularly helpful for graduate students as a tool for research.