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Robust Regression and Outlier Detection by Peter J Rousseeuw
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Robust Regression and Outlier Detection

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Description

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.

Author Biography:

Peter J. Rousseeuw, PhD, is currently a Professor at the University of Antwerp in Belgium. He received his PhD in Statistics in 1981. His research interests include the influence function approach to robust statistics and cluster analysis. Annick M. Leroy is affiliated with Vrije University in Brussels, Belgium.
Release date NZ
September 22nd, 2003
Audience
  • Professional & Vocational
Pages
360
Dimensions
157x229x16
ISBN-13
9780471488552
Product ID
2082933

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