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.
‘This is a nice book containing a wealth of information, much of
it due to the authors. . . . If an instructor designing such a
course wanted a textbook, this book would be the best choice
available. . . . There are many stimulating exercises, and the book
also contains an excellent index and an extensive list of
references.’
–Technometrics
‘[This] book should be read carefully by anyone who is
interested in dealing with statistical models in a realistic
fashion.’
–American Scientist
Introducing concepts, theory, and applications, Robust
Statistics is accessible to a broad audience, avoiding
allusions to high-powered mathematics while emphasizing ideas,
heuristics, and background. The text covers the approach based on
the influence function (the effect of an outlier on an estimater,
for example) and related notions such as the breakdown point. It
also treats the change-of-variance function, fundamental concepts
and results in the framework of estimation of a single parameter,
and applications to estimation of covariance matrices and
regression parameters.
Table des matières
1. Introduction and Motivation.
2. One-Dimensional Estimators.
3. One-Dimensional Tests.
4. Multidimensional Estimators.
5. Estimation of Covariance Matrices and Multivariate
Location.
6. Linear Models: Robust Estimation.
7. Linear Models: Robust Testing.
8. Complements and Outlook.
References.
Index.
A propos de l’auteur
FRANK R. HAMPEL, Ph D, is Professor of Statistics in the
Department of Mathematics at the Swiss Federal Institute of
Technology (ETH) Zurich, Switzerland.
ELVEZIO M. RONCHETTI, Ph D, is Professor of Statistics in
the Department of Econometrics at the University of Geneva in
Switzerland.
PETER J. ROUSSEEUW, Ph D, is Professor in the Department
of Mathematics and Computer Science at the University of Antwerp in
Belgium.
WERNER A. STAHEL, Ph D, is Professor at the Swiss Federal
Institute of Technology (ETH) Zurich, Switzerland.
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