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Outlier Detection Using Dynamic Plots

동적 그림을 이용한 이상치 검색

Ahn, Byung-Jin;Seo, Han-Son
안병진;서한손

  • Received : 20110800
  • Accepted : 20110900
  • Published : 2011.10.31

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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Cited by

  1. Outlier detection using Grubb test and Cochran test in clinical data vol.23, pp.4, 2012, https://doi.org/10.7465/jkdi.2012.23.4.657
  2. Clustering Observations for Detecting Multiple Outliers in Regression Models vol.25, pp.3, 2012, https://doi.org/10.5351/KJAS.2012.25.3.503

Acknowledgement

Supported by : 건국대학교