A comparison of multiple outlier detection methods for regression data


Billor N., KIRAL G.

COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, cilt.37, ss.521-545, 2008 (SCI İndekslerine Giren Dergi) identifier identifier

  • Cilt numarası: 37 Konu: 3
  • Basım Tarihi: 2008
  • Doi Numarası: 10.1080/03610910701812352
  • Dergi Adı: COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION
  • Sayfa Sayıları: ss.521-545

Özet

The problem of outliers in statistical data has attracted many researchers for a long time. Consequently, numerous outlier detection methods have been proposed in the statistical literature. However, no consensus has emerged as to which method is uniformly better than the others or which one is recommended for use in practical situations. In this article, we perform an extensive comparative Monte Carlo simulation study to assess the performance of the multiple outlier detection methods that are either recently proposed or frequently cited in the outlier detection literature. Our simulation experiments include a wide variety of realistic and challenging regression scenarios. We give recommendations on which method is superior to others under what conditions.