ABSTRACT
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.
MATHEMATICS SUBJECT CLASSIFICATION:
Acknowledgment
The authors are thankful to the editor and referee for their constructive and valuable suggestions and comments that have improved the presentation of the paper greatly.