PETER J.ROUSSEEUW – ROBUST REGRESSION AND OUTLIER DETECTION

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The writing style is informal and clear. The book is a keeper. There is mathematical geology.

This book should be added to the libraries of both students and professionals. The book is useful for the graduate student because it emphasizes both the philosophy and practice of robustness in regression settings, and it provides excellent examples of precise, logical proof of theorems. The aim of the book is to make robust regression available for everyday statistical practice. All of the necessary ingredients have been included. The American Statistical Association journal.

TABLE OF CONTENTS

1. Introduction.
2. Simple Regression.
3. Multiple Regression.
4. The Special Case of One-Dimensional Location.
5. Algorithms.
6. Outlier Diagnostics.
7. Related Statistical Techniques.

There are references.

There is a table of data sets.

Index.

REVIEWS

A wonderful book about methods of identifying outliers. J. Statistical computation and simulation. July 2005

Peter J.Rousseeuw is the author of Robust Regression and Outlier Detection.

Peter J.Rousseeuw is the author of Robust Regression and Outlier Detection.