Robust regression and outlier detection
Peter J. Rousseeuw, Annick M. Leroy
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.
Kategori:
Tahun:
1987
Penerbit:
Wiley
Bahasa:
english
Halaman:
347
ISBN 10:
0471725374
ISBN 13:
9780471852339
Nama seri:
Wiley series in probability and mathematical statistics. Applied probability and statistics
File:
PDF, 15.16 MB
IPFS:
,
english, 1987