bacon: An effective way to detect outliers in multivariate data using Stata (and Mata)
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.
Volume (Year): 10 (2010)
Issue (Month): 3 (September)
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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- 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.
- Christopher F Baum, 2009. "Using Mata to work more effectively with Stata: A tutorial," German Stata Users' Group Meetings 2009 06, Stata Users Group.
- Kit Baum, 2008. "Using Mata to work more effectively with Stata: A tutorial," United Kingdom Stata Users' Group Meetings 2008 11, Stata Users Group.
- 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. Full references (including those not matched with items on IDEAS)