The problem of multicollinearity and outliers in the dataset can strongly distort ordinary least squares 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 Mestimator. Furthermore, we give a numerical example and a simulation study to illustrate some of the theoretical results.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.