Titlebook: Directions in Robust Statistics and Diagnostics; Part II Werner Stahel,Sanford Weisberg Conference proceedings 1991 Springer-Verlag New Yor

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General Approaches to Stepwise Identification of Unusual Values in Data Analysis, directly (via some detection procedure). This paper summarizes the backwards-stepping approach to the detection of unusual values in a data set. This approach has the advantages of simplicity of application, flexibility, and resistance to masking effects. Application to univariate, multivariate, an

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Adaptive Efficient Weighted Least Squares With Dependent Observations,atrix of the ordinary least squares (OLS) estimator for the parameters of the linear regression model despite the possible presence of heteroskedasticity of unknown form. In this sense, such covariance matrix estimators are “robust” to unequal scale of the regression errors. Cragg [1983] proposed pa

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Regression Quantile Diagnostics for Multiple Outliers, it is shown that the “l(fā)east median of squares” estimator is . an elemental solutions (i.e., fit exactly by . observations), but is determined to have exactly . + 1) equal residuals when there are . parameters.

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Robust Testing of Functionals,ity, however, degenerates to some kind of unbiasedness since all other “estimator tests” .(.) with . ≠ . achieve asymptotic minimum power zero..The selection of the functional .(.) to be tested leads to nontrivial optimality problems. In the one dimensional, onesided case,.one may want to test ε-con

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Consumer Datesware,on sense and the fact that not all initial analysis should be robust. It seems possible that the frequent use and poor understanding of regression may make it the easiest place for robust techniques (adequately enhanced by graphical diagnosis and procedures to help choose expressions) to penetrate d

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0940-6573 e the required inferences. If, how- ever, the parametric model is not completely correct, then the standard inferential methods may not give reasonable answers.978-1-4612-8772-8978-1-4612-4444-8Series ISSN 0940-6573 Series E-ISSN 2198-3224