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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,d regression data, as well as other problems, is discussed. Simulations are used to investigate the properties of this strategy for data analysis. It is shown that identification of unusual values using appropriate detection procedures can be considerably more effective than indirect detection using a robust analysis.
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https://doi.org/10.1057/9780230378612igation of omitted predictor variables. Techniques are discussed, together with details of their routine implementation within a knowledge-based front-end system GLIMPSE. Wherever possible, graphical displays are used; complemented by formal test statistics as appropriate.
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Glimpse: An Assessor of GLM Misspecification,igation of omitted predictor variables. Techniques are discussed, together with details of their routine implementation within a knowledge-based front-end system GLIMPSE. Wherever possible, graphical displays are used; complemented by formal test statistics as appropriate.
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Adaptive Efficient Weighted Least Squares With Dependent Observations,asymptotic variance than OLS. However, Cragg’s estimators are not guaranteed to have minimum asymptotic variance, so the presence of heteroskedasticity of unknown form can still have adverse consequences for the power of tests based on these estimators.
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Mark R. Nerlich,Volker Kirchberg robust analyses and surveys past studies of it. With increasing speed of computation, resampling techniques have become feasible solutions to this studentizing problem. Some discussion of these techniques is also offered. To illustrate the discussion a Monte Carlo study of several experiments is included.
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