A New Procedure of Generalized STAR Modelling using IAcM Approach

A new procedure of space time modeling through the Invers of Autocovariance Matrix (IAcM) is proposed. By knowing the IAcM behaviors on behalf of the Generalized Space Time Autoregressive (GSTAR) process stationarity, we may find an appropriate model to space time data series. This method should become a completion to the Space Time ACF and PACF methods in identifying space time models. For study case, we apply the GSTAR models to the monthly tea production of some plantations in West Java, Indonesia.