Robust Statistics
Wiley Series in Probability and Statistics
2. Edition March 2009
384 Pages, Hardcover
Handbook/Reference Book
Short Description
Robust Statistics, Second Edition includes four new chapters on the following topics: robust tests; small sample asymptotics; breakdown point; and Bayesian robustness. A new section on time series has also been included. The first edition of this book was the first systematic, book-length treatment of robust statistics. The book begins with a general introduction and the formal mathematical background behind qualitative and quantitative robustness. A solid foundation of robust statistics for both the theoretical and the applied statistician is provided. The book successfully reorganizes, summarizes, and extends information that has been available in part thus far. Concepts are stressed throughout rather than mathematical completeness, and selected numerical algorithms for computing robust estimates, as well as convergence proofs, are provided. Quantitative robustness information for a variety of estimates is contained within tables throughout.
A new edition of the classic, groundbreaking book on robust statistics
Over twenty-five years after the publication of its predecessor, Robust Statistics, Second Edition continues to provide an authoritative and systematic treatment of the topic. This new edition has been thoroughly updated and expanded to reflect the latest advances in the field while also outlining the established theory and applications for building a solid foundation in robust statistics for both the theoretical and the applied statistician.
A comprehensive introduction and discussion on the formal mathematical background behind qualitative and quantitative robustness is provided, and subsequent chapters delve into basic types of scale estimates, asymptotic minimax theory, regression, robust covariance, and robust design. In addition to an extended treatment of robust regression, the Second Edition features four new chapters covering:
* Robust Tests
* Small Sample Asymptotics
* Breakdown Point
* Bayesian Robustness
An expanded treatment of robust regression and pseudo-values is also featured, and concepts, rather than mathematical completeness, are stressed in every discussion. Selected numerical algorithms for computing robust estimates and convergence proofs are provided throughout the book, along with quantitative robustness information for a variety of estimates. A General Remarks section appears at the beginning of each chapter and provides readers with ample motivation for working with the presented methods and techniques.
Robust Statistics, Second Edition is an ideal book for graduate-level courses on the topic. It also serves as a valuable reference for researchers and practitioners who wish to study the statistical research associated with robust statistics.
Preface to First Edition.
1. Generalities.
2. The Weak Topology and its Metrization.
3. The Basic Types of Estimates.
4. Asymptotic Minimax Theory for Estimating Location.
5. Scale Estimates.
6. Multiparameter Problems, in Particular Joint Estimation of Location and Scale.
7. Regression.
8. Robust Covariance and Correlation Matrices.
9. Robustness of Design.
10. Exact Finite Sample Results.
11. Finite Sample Breakdown Point.
12. Infinitesimal Robustness.
13. Robust Tests.
14. Small Sample Asymptotics.
15. Bayesian Robustness.
References.
Index.
