In this paper, we consider one-step outlier identifiation rules for multivariate data, generalizing the concept of so-called alpha outlier identifiers, as presented in Davies and Gather (1993) for the case of univariate samples. We investigate, how the finite-sample breakdown points of estimators used in these identification rules influence the masking behaviour of the rules
Outlier identification is important in many applications of multivariate analysis. Either because th...
Researchers often lack knowledge about how to deal with outliers when analyzing their data. Even mor...
Researchers often lack knowledge about how to deal with outliers when analyzing their data. Even mor...
In this paper, we consider one-step outlier identification rules for multivariate data, generalizing...
In their paper, Davies and Gather (1993) formalized the task of outlier identification, considering ...
In investigations on the behaviour of robust estimators, typically their consistency and their asymp...
In this paper, the task of identifying outliers in exponential samples is treated conceptionally in ...
The aim of detecting outliers in a multivariate sample can be pursued in different ways. We investig...
The aim of detecting outliers in a multivariate sample can be pursued in different ways. We investig...
One approach to identifying outliers is to assume that the outliers have a different distribution fr...
One approach to identifying outliers is to assume that the outliers have a different distribution fr...
In this paper we consider the problem of identifying outliers in exponential samples with stepwise p...
Multivariate outliers are usually identified by means of robust distances. A statistically principl...
In extending univariate outlier detection methods to higher dimension, various issues arise: limited...
Multivariate outlier identification requires the choice of reliable cut-off points for the robust di...
Outlier identification is important in many applications of multivariate analysis. Either because th...
Researchers often lack knowledge about how to deal with outliers when analyzing their data. Even mor...
Researchers often lack knowledge about how to deal with outliers when analyzing their data. Even mor...
In this paper, we consider one-step outlier identification rules for multivariate data, generalizing...
In their paper, Davies and Gather (1993) formalized the task of outlier identification, considering ...
In investigations on the behaviour of robust estimators, typically their consistency and their asymp...
In this paper, the task of identifying outliers in exponential samples is treated conceptionally in ...
The aim of detecting outliers in a multivariate sample can be pursued in different ways. We investig...
The aim of detecting outliers in a multivariate sample can be pursued in different ways. We investig...
One approach to identifying outliers is to assume that the outliers have a different distribution fr...
One approach to identifying outliers is to assume that the outliers have a different distribution fr...
In this paper we consider the problem of identifying outliers in exponential samples with stepwise p...
Multivariate outliers are usually identified by means of robust distances. A statistically principl...
In extending univariate outlier detection methods to higher dimension, various issues arise: limited...
Multivariate outlier identification requires the choice of reliable cut-off points for the robust di...
Outlier identification is important in many applications of multivariate analysis. Either because th...
Researchers often lack knowledge about how to deal with outliers when analyzing their data. Even mor...
Researchers often lack knowledge about how to deal with outliers when analyzing their data. Even mor...
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