Abstract

Abstract A method for modeling and fitting multivariate spatial time series data based on current spatial methodology coupled with the parameterization of the ARMAX model is presented. Because of the physical constraints imposed on multivariate data collection in both space and time, the estimation and identification procedures tolerate general patterns of missing or incomplete data.

Full Text
Published version (Free)

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 call