[Wiley Series in Probability and Statistics] Robust Statistics (Theory and Methods) || Asymptotic Theory of M-estimates

✍ Scribed by Maronna, Ricardo A.; Martin, R. Douglas; Yohai, Víctor J.

• Publisher: John Wiley & Sons, Ltd
• Year: 2006
• Tongue: English
• Weight: 312 KB
• Edition: 1
• Category: Article
• ISBN: 0470010924
• DOI: 10.1002/0470010940.ch10

✦ Synopsis

Robust Statistics Sets Out To Explain The Use Of Robust Methods And Their Theoretical Justification. It Provides An Up-to-date Overview Of The Theory And Practical Application Of Robust Statistical Methods In Regression, Multivariate Analysis, Generalized Linear Models And Time Series. Robust Statistics Aims To Stimulate The Use Of Robust Methods As A Powerful Tool To Increase The Reliability And Accuracy Of Statistical Modelling And Data Analysis. It Is Ideal For Researchers, Practitioners And Graduate Students Of Statistics, Electrical, Chemical And Biochemical Engineering, And Computer Vision. There Is Also Much To Benefit Researchers From Other Sciences, Such As Biotechnology, Who Need To Use Robust Statistical Methods In Their Work.--jacket. Location And Scale -- Measuring Robustness -- Linear Regression 1 -- Linear Regression 2 -- Multivariate Analysis -- Generalized Linear Models -- Time Series -- Numerical Algorithms -- Asymptotic Theory Of M-estimates -- Robust Methods In S-plus -- Description Of Data Sets. Ricardo A. Maronna, R. Douglas Martin, Víctor J. Yohai. Includes Bibliographical References (p. [383]-396) And Index.