COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, vol.46, no.3, pp.1958-1973, 2017 (SCI-Expanded)
This 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.