Certain Aspects of Generalized Box-Jenkins Models

Abstract

We define a class of models that are generalizations of regression models and moving average-autoregressive time series models. Then we investigate the asymptotic and computational properties of the maximum likelihood estimator, with numerical examples. The main conclusion is that care must be exercised when using simple approximations to the covariance matrix of the estimates.