A modified ridge m-estimator for linear regression model with multicollinearity and outliers
MetadataShow full item record
CitationErtaş, 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
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.