Robust Liu-type estimator for regression based on M-estimator

Ertas H., KAÇIRANLAR S., GÜLER H.

COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, cilt.46, sa.5, ss.3907-3932, 2017 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 46 Sayı: 5
  • Basım Tarihi: 2017
  • Doi Numarası: 10.1080/03610918.2015.1045077
  • Dergi Adı: COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.3907-3932
  • Anahtar Kelimeler: Biased estimation, Multicollinearity, Outliers, Robust Regression, 62J05, 62J07, RIDGE-REGRESSION
  • Çukurova Üniversitesi Adresli: Evet

Özet

The problem of multicollinearity and outliers in the dataset can strongly distort ordinary least-square estimates and lead to unreliable results. We propose a new Robust Liu-type M-estimator to cope with this combined problem of multicollinearity and outliers in the y-direction. Our new estimator has advantages over two-parameter Liu-type estimator, Ridge-type M-estimator, and M-estimator. Furthermore, we give a numerical example and a simulation study to illustrate some of the theoretical results.