Univariate and multivariate outlier identification for skewed or heavy-tailed distributions
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.
View all articles by these authors:
Vincenzo Verardi, Catherine Vermandele
View all articles with these keywords:
gboxplot, sdasym, box plot, generalized box plot, outlier detection, outlyingness, projection, Tukey g-and-h distribution
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