Robust Regression and Outlier Detection

Peter J. Rousseeuw, Annick M. Leroy (Autoren)

Buch | Hardcover

352 Seiten

1987
John Wiley & Sons Inc (Verlag)
978-0-471-85233-9 (ISBN)

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Provided here is an applications-oriented introduction to robust regression and outlier detection, emphasising 'high- breakdown' methods which can cope with a sizeable fraction of contamination.

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.

Simple Regression. Multiple Regression. The Special Case of One--Dimensional Location. Algorithms. Outlier Diagnostics. Related Statistical Techniques. References. Index.

Erscheint lt. Verlag	2.12.1987
Reihe/Serie	Wiley Series in Probability & Mathematical Statistics: Applied Probability & Statistics
Zusatzinfo	Ill.
Verlagsort	New York
Sprache	englisch
Maße	159 x 236 mm
Gewicht	567 g
Themenwelt	Mathematik / Informatik ► Mathematik ► Angewandte Mathematik
ISBN-10	0-471-85233-3 / 0471852333
ISBN-13	978-0-471-85233-9 / 9780471852339
Zustand	Neuware