The article introduces a new way to estimate regression parameters in a multivariate linear model. The researchers found that this new estimator has a lower mean square error compared to the traditional least square estimator when the design matrix is not ideal. They also showed that this new estimator is a valid choice. Additionally, they discussed the characteristics of the mean square residual error of the new estimator.