The article explores a method to analyze data with outliers in linear regression. By adding a parameter for outliers to the model, the researchers aim to estimate both coefficients and outliers efficiently. They use a specific penalty for coefficients and various penalties for outliers. An optimization algorithm is introduced to solve the estimation problem. The algorithm is shown to converge and recover the true coefficients accurately.