Robust Liu-type estimator for regression based on M-estimator
Yükleniyor...
Dosyalar
Tarih
2017
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Taylor and Francis Ltd.
Erişim Hakkı
info:eu-repo/semantics/closedAccess
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.
Açıklama
Hasan Ertas was supported by Cukurova University Academic Research Projects (FEF2013D15).
Anahtar Kelimeler
Biased estimation, Multicollinearity, Outliers, Robust Regression
Kaynak
Communications in Statistics - Simulation and Computation
WoS Q Değeri
N/A
Scopus Q Değeri
N/A
Cilt
46
Sayı
5
Künye
Ertaş, H., Kaçıranlar, S., & Güler, H. (2017). Robust Liu-type estimator for regression based on M-estimator. Communications in Statistics-Simulation and Computation, 46(5), 3907-3932.
