Leroy, Annick M.
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.
Keywords: MATHEMATICS / Probability & Statistics / General MAT029000
- Author(s)
- Leroy, Annick M.
- Rousseeuw, Peter J.
- Publisher
- John Wiley and Sons, Inc.
- Publication year
- 2005
- Language
- en
- Edition
- 1
- Series
- Wiley Series in Probability and Statistics
- Category
- Natural Sciences
- Format
- Ebook
- eISBN (PDF)
- 9780471725374
- Printed ISBN
- 9780471852339