05: An Unbiased Convex Estimator for Classical Linear Regression Model Using Prior Information

Music City Center 

We propose an unbiased restricted estimator that leverages prior information to enhance estimation efficiency for the linear regression model. The statistical properties of the proposed estimator are rigorously examined, highlighting its superiority over several existing methods. A simulation study is conducted to evaluate the performance of the estimators, and real-world data on total national research and development expenditures by country are analyzed to illustrate the findings. Both the simulation results and real-data analysis demonstrate that the proposed estimator consistently outperforms the alternatives considered in this study.

Linear model

MSE

Unbiased ridge estimator

Restricted least-squares estimator

Multicollinearity 

Section on Statistical Computing