Regression models with stationary autocorrelated errors

Abstract

In multiple regression model, it usually assumed that the error terms are independent. However, ignoring the autocorrelation or dependency between the errors is risky with respect to validity because of the damage that is done to the model. Autocorrelated error terms require modification of the usual methods of the estimation. One parametric approach that may be used to avoid this problem is to consider an ARMA model for the errors of the model then regressing a transformed model