Abstract
Soltani and Mohammadpour (2009) presented an algorithm for the best linear interpolator of unrecorded innovations in discrete time multivariate second order stationary processes. In this paper, we develop an interpolation procedure for multivariate ARMA processes, using the interpolation of the underlying innovations. In this case, the coefficients of the model and the past and future multivariate data are the inputs of the algorithm. We also obtain a closed form expression for the best linear interpolator of single value for MA(1) and AR(1) time series models.
Sign-in/Register to access full text options 
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.
