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Deepest regression (DR) is a method for linear regression introduced by P. J. Rousseeuw and M. Hubert (1999, J. Amer. Statis. Assoc.94, 388-402). The DR method is defined as the fit with largest regression depth relative to the data. In this paper we show that DR is a robust method, with...
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This paper examines the distribution of Belgian consumer prices and its interaction with aggregate inflation over the period June 1976-September 2000. Given the fat-tailed nature of this distribution, both classical and robust measures of location, scale and skewness are presented. We found a...
Persistent link: https://www.econbiz.de/10005060076
This paper describes the incorporation of seven stand-alone clustering programs into S-PLUS, where they can now be used in a much more flexible way. The original Fortran programs carried out new cluster analysis algorithms introduced in the book of Kaufman and Rousseeuw (1990). These clustering...
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In this paper we propose several goodness-of-fit tests based on robust measures of skewness and tail weight. They can be seen as generalisations of the Jarque-Bera test (Bera and Jarque, 1981) based on the classical skewness and kurtosis, and as an alternative to the approach of Moors et al....
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Motivated by the notion of regression depth (Rousseeuw and Hubert, 1996) we introduce thecatline, a new method for simple linear regression. At any bivariate data setZn={(xi, yi);i=1, ..., n} its regression depth is at leastn/3. This lower bound is attained for data lying on a convex or...
Persistent link: https://www.econbiz.de/10005093787