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

Vincenzo Verardi and Catherine Vermandele ()
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Catherine Vermandele: Université libre de Bruxelles

Stata Journal, 2018, vol. 18, issue 3, 517-532

Abstract: 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.

Keywords: gboxplot; sdasym; box plot; generalized box plot; outlier detection; outlyingness; projection; Tukey g-and-h distribution (search for similar items in EconPapers)
Date: 2018
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