Ertaş, HasanKaçıranlar, SelahattinGüler, Hüseyin2021-04-152021-04-152017Ertaş, 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.https://hdl.handle.net/11494/2983Hasan Ertas was supported by Cukurova University Academic Research Projects (FEF2013D15).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.eninfo:eu-repo/semantics/closedAccessBiased estimationMulticollinearityOutliersRobust RegressionArticle46539073932N/AN/A