Robust Statistics

Передня обкладинка
John Wiley & Sons, 2004 - 308 стор.
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.
 

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Зміст

GENERALITIES
1
THE WEAK TOPOLOGY AND ITS METRIZATION
20
THE BASIC TYPES OF ESTIMATES
43
ASYMPTOTIC MINIMAX THEORY FOR ESTIMATING
73
SCALE ESTIMATES
107
6
124
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Про автора (2004)

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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