Using Corrected Biased for Developing New Weighted Mixed Estimator for Linear Regression Model

A study of a new type of corrected weighted mixed estimator has been proposed for the linear stochastic restricted regression model. In this approach, the sample data is not given the same weight as the historical data. The suggested estimator bias, variance matrices, and mean square error (MSE) are computed and compared in this work. This estimator’s performance was compared to other estimators using the mean square error criteria. Lastly, a numerical example was analyzed to shed further light on how the performance of the new estimator was evaluated.