Robust Regression and Outlier Detection
Rousseeuw
€ 178.47
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Description for Robust Regression and Outlier Detection
Paperback. This comprehensive book provides readers with an applications--oriented introduction to robust regression and outlier detection - emphasising A"high--breakdownA" 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. Series: Wiley Series in Probability and Statistics. Num Pages: 360 pages, Illustrations. BIC Classification: PDE; RBG; TBJ. Category: (P) Professional & Vocational. Dimension: 153 x 231 x 22. Weight in Grams: 560.
WILEY-INTERSCIENCE PAPERBACK SERIES
WILEY-INTERSCIENCE PAPERBACK SERIES
The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists.
"The writing style is clear and informal, and much of the discussion is oriented to application. In short, the book is a keeper."
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Show LessProduct Details
Format
Paperback
Publication date
2003
Publisher
John Wiley and Sons Ltd United States
Number of pages
360
Condition
New
Series
Wiley Series in Probability and Statistics
Number of Pages
368
Place of Publication
, United States
ISBN
9780471488552
SKU
V9780471488552
Shipping Time
Usually ships in 7 to 11 working days
Ref
99-50
About Rousseeuw
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.
Reviews for Robust Regression and Outlier Detection
"…a wonderful book about methods of identifying outliers and then developing robust regression." (Journal of Statistical Computation and Simulation, July 2005)