Two Stochastic Restricted Principal Components Regression Estimator in Linear Regression

Abstract

In this article, we propose two stochastic restricted principal components regression estimator by combining the approach followed in obtaining the ordinary mixed estimator and the principal components regression estimator in linear regression model. The performance of the two new estimators in terms of matrix MSE criterion is studied. We also give an example and a Monte Carlo simulation to show the theoretical results.

Keywords:

• Multicollinearity
• Ordinary least squares estimator
• Ordinary mixed estimator
• Principal components regression estimator

Mathematics Subject Classification:

• 62J07

Acknowledgment

The authors wish to thank the referee and Editor for helpful suggestions and comments which helped to improve the quality of this article. This work was supported by the National Natural Science Foundation of China (No. 11171361).