Here is a brief, and easy-to-follow introduction and overview of robust statistics. Peter 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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Here is a brief, and easy-to-follow introduction and overview of robust statistics. Peter 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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Add this copy of Robust Statistical Procedures (Cbms-Nsf Regional to cart. $114.85, new condition, Sold by GridFreed rated 4.0 out of 5 stars, ships from North Las Vegas, NV, UNITED STATES, published 1987 by Society for Industrial and Applied Mathematics.
Edition:
1987, Society for Industrial and Applied Mathematics (SIAM)
