A modified ridge m-estimator for linear regression model with multicollinearity and outliers
Yükleniyor...
Dosyalar
Tarih
2018
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Taylor & Francis Inc
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
The ordinary least-square estimators for linear regression analysis with multicollinearity and outliers lead to unfavorable results. In this article, we propose a new robust modified ridge M-estimator (MRME) based on M-estimator (ME) to deal with the combined problem resulting from multicollinearity and outliers in the y-direction. MRME outperforms modified ridge estimator, robust ridge estimator and ME, according to mean squares error criterion. Furthermore, a numerical example and a Monte Carlo simulation experiment are given to illustrate some of the theoretical results.
Açıklama
Anahtar Kelimeler
Biased estimator, Multicollinearity, Outliers, Robust estimator
Kaynak
Communications in Statistics-Simulation and Computation
WoS Q Değeri
N/A
Scopus Q Değeri
N/A
Cilt
47
Sayı
4
Künye
Ertaş, H. (2018). A modified ridge m-estimator for linear regression model with multicollinearity and outliers. Communications in Statistics-Simulation and Computation, 47(4), 1240-1250, DOI: 10.1080/03610918.2017.1310231
