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http://dx.doi.org/10.5351/KJAS.2011.24.5.979

Outlier Detection Using Dynamic Plots  

Ahn, Byung-Jin (Department of Applied Statistics, Konkuk University)
Seo, Han-Son (Department of Applied Statistics, Konkuk University)
Publication Information
The Korean Journal of Applied Statistics / v.24, no.5, 2011 , pp. 979-986 More about this Journal
Abstract
A linear regression method is commonly used to analyze data because of its simplicity and applicability; however, it is well known that data may contain some outliers and influential cases that may have a harmful effect on a statistical analysis. Thus detection and examination of outliers or influential cases are important parts of data analysis. In detecting multiple outliers, masking effects usually occur and make it difficult to identify the true outliers. We propose to use dynamic plots as a method resistant to masking effect. The procedure using dynamic plots is useful to find appropriate basic sets with which a dependent outliers detection method start and detect a true outliers set. Examples are given to demonstrate the effectiveness of the suggested idea.
Keywords
Dynamic graphics; linear regression model; outliers; residual plots;
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