Abstract
This paper gives an expression for the minimum mean squared error predictor of the single equation ARMAX model when all the parameters are known. A formula is then derived for the asymptotic prediction mean squared error when the parameters are replaced by their maximum likelihood estimates. These general results are then specialised to the regression model with ARMA errors; for this case we also consider the properties of an alternative predictor which can sometimes be marginally more efficient than the conventional predictor.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
