On the Robust Parameter Estimation Method for Linear Model with Autocorrelated Errors in the Presence of High Leverage Points and Outliers in the Y-Direction

In the existence of autocorrelation problem, the Ordinary Least Squares (OLS) estimates become incompetent. The Cochrane - Orcutt Prais -Winsten iterative method (COPW) is the most widely used remedial measure to rectify this problem. However, this iterative procedure is based on the OLS estimates, which is not resistant and easily in�uenced
by high leverage points (outliers in the x-direction) and outliers in they-direction. The COPW based on MM estimator is developed to remedy both problems of autocorrelation and high leverage points. Nevertheless, MM estimator does not perform well in the presence of bad leverage points. In this paper, we propose to improvise the Cochrane-Orcutt