Tabakan, GülinÖzkale, Revan13.07.20192019-07-1613.07.20192019-07-1620170361-09181532-4141https://doi.org/10.1080/03610918.2015.1026988https://hdl.handle.net/20.500.12451/4840This article is concerned with the parameter estimation in partly linear regression models when the errors are dependent. To overcome the multicollinearity problem, a generalized Liu estimator is proposed. The theoretical properties of the proposed estimator and its relationship with some existing methods designed for partly linear models are investigated. Finally, a hypothetical data is conducted to illustrate some of the theoretical results.eninfo:eu-repo/semantics/closedAccessLeast SquaresLiu SstimatorPartly Linear ModelsRidge EstimatorSmoothing ParameterArticle4631958197310.1080/03610918.2015.1026988Q2WOS:000398114600022N/A