This article considers an optimal procedure of identifying the influential observations in a regression model with AR(2) errors. It develops some diagnostic techniques using a “hat matrix”. The likelihood ratio and F-test statistic have been discussed and an example of a constant mean model with AR(2) error shows its practical application in time series.