The minimum density power divergence method provides a robust estimate in the face of a situation where the dataset includes a number of outlier data.

In this study, we introduce and use a robust minimum density power divergence estimator to estimate the parameters of the linear regression model and then with some numerical examples of linear regression model, we show the robustness of this estimator in the face of a dataset which includes a number of outliers.