The first systematic, book-length treatment of the subject. Begins with a general introduction and the formal mathematical background behind qualitative and quantitative robustness. Stresses concepts. Provides selected numerical algorithms for computing robust estimates, as well as convergence proofs. Tables contain quantitative robustness information for a variety of estimates.
Содержание
1. Generalities.
2. The Weak Topology and Its Metrization.
3. The Basic Types of Estimates.
4. Asymptotic Minimax Theory for Estimating a Location
Parameter.
5. Scale Estimates.
6. Multiparameter Problems, In Particular Joint Estimation of
Location and Scale.
7. Regression.
8. Robust Covariance and Correlation Matrices.
9. Rubustness of Design.
10. Exact Finite Sample Results.
11. Miscellaneous Topics.
References.
Index.
Об авторе
Peter J. Huber was formerly a Professor of Statistics at Harvard University and ETH Zurich. Dr. Huber received his Ph.D. in Mathematics from ETH Zurich in 1961.
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