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bacon: An effective way to detect outliers in multivariate data using Stata (and Mata)

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  • Sylvain Weber

    (University of Geneva)

Abstract

Identifying outliers in multivariate data is computationally intensive. The bacon command, presented in this article, allows one to quickly identify out- liers, even on large datasets of tens of thousands of observations. bacon constitutes an attractive alternative to hadimvo, the only other command available in Stata for the detection of outliers. Copyright 2010 by StataCorp LP.

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  • Sylvain Weber, 2010. "bacon: An effective way to detect outliers in multivariate data using Stata (and Mata)," Stata Journal, StataCorp LP, vol. 10(3), pages 331-338, September.
    • Handle: RePEc:tsj:stataj:v:10:y:2010:i:3:p:331-338
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    References listed on IDEAS

    as
    1. Kit Baum, 2008. "Using Mata to work more effectively with Stata: A tutorial," Fall North American Stata Users' Group Meetings 2008 7, Stata Users Group.
    2. Billor, Nedret & Hadi, Ali S. & Velleman, Paul F., 2000. "BACON: blocked adaptive computationally efficient outlier nominators," Computational Statistics & Data Analysis, Elsevier, vol. 34(3), pages 279-298, September.
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