Abstract
In this article, a generalized restricted difference-based ridge estimator is defined for the vector parameter in a partial linear model when the errors are dependent. It is suspected that some additional linear constraints may hold on to the whole parameter space. The estimator is a generalization of the well-known restricted least-squares estimator and is confined to the (affine) subspace which is generated by the restrictions. The risk functions of the proposed estimators are derived under balanced loss function. Finally, the performance of the new estimators is evaluated by a simulated data set.
Acknowledgements
The authors would like to thank the anonymous referee and the Associate Editor for their constructed suggestions which significantly improved the presentation of the article. Partial support from the Ordered and Spatial Center of Excellence of Ferdowsi University of Mashhad, Iran is acknowledged.