A method for estimating a forecasting model’s parameters that drops the assumption of independence of errors and uses an estimate of the errors’ interrelationships. In the Ordinary-Least-Squares (OLS) estimation of a forecasting model, it is assumed that errors are independent of each other and do not suffer from heteroscedasticity. Whether GLS is useful to forecasters has not been established. OLS generally provides sufficient accuracy.