Asymptotic Statistics
Asymptotic Statistics
$71.99
USDHere 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.
- Based on notes from graduate and master's level courses taught by the author in Europe and in the US
- Mathematically rigorous yet practical
- Coverage of a wide range of classical and recent topics
Reviews & endorsements
'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
Product details
June 2000Paperback
9780521784504
462 pages
255 × 179 × 28 mm
0.81kg
14 b/w illus. 8 tables
Available
Table of Contents
- 1. Introduction
- 2. Stochastic convergence
- 3. The delta-method
- 4. Moment estimators
- 5. M- and Z-estimators
- 6. Contiguity
- 7. Local asymptotic normality
- 8. Efficiency of estimators
- 9. Limits of experiments
- 10. Bayes procedures
- 11. Projections
- 12. U-statistics
- 13. Rank, sign, and permutation statistics
- 14. Relative efficiency of tests
- 15. Efficiency of tests
- 16. Likelihood ratio tests
- 17. Chi-square tests
- 18. Stochastic convergence in metric spaces
- 19. Empirical processes
- 20. The functional delta-method
- 21. Quantiles and order statistics
- 22. L-statistics
- 23. The bootstrap
- 24. Nonparametric density estimation
- 25. Semiparametric models.
