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

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https://doi.org/10.1007/978-3-319-43536-7Research directions in robust statistics are listed and partly commented. The intention is to help stimulating research in topics which are important according to the author’s perception. The reference list includes more than 500 items, mainly of the years 1985–1990.

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Regression Diagnostics for Rank-Based Methods II,Some diagnostics based on .-estimates of regression coefficients are developed. .-estimates are not as sensitive to outliers in the . -space as least squares estimates. In data sets with several such outliers, the .-diagnostics have a greater chance of detecting these outliers. Robust analogues of the external .-statistic and . are developed.

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Robust Multivariate Spectral Analysis of the EEG,The multichannel electroencephalogram (EEG), obtained from an array of scalp electrodes, can be looked at as a realization of a multivariate stochastic process, whose second order properties are investigated by the methods of spectral analysis.

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Mark R. Nerlich,Volker Kirchberg squares analysis in analyzing linear models. Much of the work done on robust analyses of linear models has concerned their asymptotic properties. To be of practical interest, though, the small sample properties of these analyses need to be ascertained. This article discusses studentization of these

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