Robust Statistical Procedures: Second Edition
yan, 1996 · CBMS-NSF Regional Conference Series in Applied Mathematics 68-kitob · SIAM
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Here is a brief, well-organized, and easy-to-follow introduction and overview of robust statistics. Huber focuses primarily on the important and clearly understood case of distribution robustness, where the shape of the true underlying distribution deviates slightly from the assumed model (usually the Gaussian law). An additional chapter on recent developments in robustness has been added and the reference list has been expanded and updated from the 1977 edition.
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