OUTLIER DETECTION BY REGRESSION DIAGNOSTICS BASED ON ROBUST PARAMETER ESTIMATES

TÜRKAN S., CETIN M. C., TOKTAMIS O.

HACETTEPE JOURNAL OF MATHEMATICS AND STATISTICS, vol.41, no.1, pp.147-155, 2012 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 41 Issue: 1
  • Publication Date: 2012
  • Journal Name: HACETTEPE JOURNAL OF MATHEMATICS AND STATISTICS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, TR DİZİN (ULAKBİM)
  • Page Numbers: pp.147-155
  • Hacettepe University Affiliated: Yes

Abstract

In this article, robust versions of some of the frequently used diagnostics are considered to identify outliers instead of the diagnostics based on the least square method. These diagnostics are Cook's distance, the Welsch-Kull distance and the Hadi measure. A simulation study is performed to compare the performance of the classical diagnostics with the proposed diagnostics based on robust M estimation to identify outliers.