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Robust regression and outlier detection PDF

347 Pages·1987·15.163 MB·English
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by Peter J. Rousseeuw, Annick M. Leroy| 1987| 347 pages| 15.163| English

About Robust regression and outlier detection

Provides an applications-oriented introduction to robust regression and outlier detection, emphasising °high-breakdown° methods which can cope with a sizeable fraction of contamination. Its self-contained treatment allows readers to skip the mathematical material which is concentrated in a few sections. Exposition focuses on the least median of squares technique, which is intuitive and easy to use, and many real-data examples are given. Chapter coverage includes robust multiple regression, the special case of one-dimensional location, algorithms, outlier diagnostics, and robustness in related fields, such as the estimation of multivariate location and covariance matrices, and time series analysis.

Detailed Information

Author:Peter J. Rousseeuw, Annick M. Leroy
Publication Year:1987
ISBN:471852333
Pages:347
Language:English
File Size:15.163
Format:PDF
Price:FREE
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