Introduction to Robust and Quasi-Robust Statistical Methods

✍ Scribed by Dr. William J. J. Rey (auth.)

• Publisher: Springer-Verlag Berlin Heidelberg
• Year: 1983
• Tongue: English
• Leaves: 246
• Series: Universitext
• Edition: 1
• Category: Library

✦ Synopsis

Overview: The first part book surveys available methods of robust and quasi-robust statistical methods. The theory is presented in an expository style and in a unifying manner which allows seemingly disparate items to find their place in a common structure. It then becomes gradually clear that the techincal requirements leading to robustness are very demanding. The second part of the book treats the methods as they are encountered in real life situations. Robustness requirements are relaxed a little and "quasi-robust" estimators are obtained; the latter are much more reliable than the standard estimators without being as difficult to handle as the as the robust estimators. Algorithms are discribed and test cases are discsssed. This second part imore importans the t for the statistician who routinely processes data sets.

✦ Table of Contents

Front Matter....Pages I-IX
Introduction and Summary....Pages 1-15
Sample spaces, distributions, estimators …....Pages 16-47
Robustness, breakdown point and influence function....Pages 48-54
The jackknife method....Pages 55-77
Bootstrap methods, sampling distributions....Pages 78-88
Front Matter....Pages 89-89
Type M estimators....Pages 90-116
Type L estimators....Pages 117-130
Type R estimator....Pages 131-133
Type MM estimators....Pages 134-189
Quantile estimators and confidence intervals....Pages 190-195
Miscellaneous....Pages 196-206
References....Pages 207-233
Back Matter....Pages 234-238

✦ Subjects

Statistics, general