Weighted Mixed Two Parameter Estimator in Multiple Linear Regression Model in the Presence of Multicollinearity

In this article, we introduce a new estimator, namely Weighted Mixed Two Parameter Estimator (WMTPE) to estimate the regression coefficients when the multicollinearity is present, and the stochastic restrictions are available in addition to the sample model. The proposed estimator is compared with some biased estimators in the Mean Square Error Matrix (MSEM) sense. To illustrate the theoretical findings, a Monte Carlo simulation study is conducted and a numerical example is used. From the theoretical and numerical results, it could be concluded that the proposed estimator performs better than other existing estimators used in this study.