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Univariate and multivariate outlier identification for skewed or heavy-tailed distributions

par Verardi, Vincenzo ;Vermandele, Catherine
Référence The Stata journal, 18, 3, page (517-532), st0533
Publication Publié, 2018

Article révisé par les pairs

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Résumé :

In univariate and in multivariate analyses, it is difficult to identify outliers in the case of skewed or heavy-tailed distributions. In this article, we propose simple univariate and multivariate outlier identification procedures that perform well with these types of distributions while keeping the computational complexity low. We describe the commands gboxplot (univariate case) and sdasym (multivariate case), which implement these procedures in Stata.