Poisson GSTAR model: Spatial temporal modeling count data follow generalized linear model and count time series models

Abstract

This paper discusses the formation of one temporal spatial model, the Generalized Space Time Autoregressive (GSTAR) model, if the data of model is count data. The development of the GSTAR model is an update or problem completion of the count data which tends to be stationary and non-normal / Gaussian data, because GSTAR model is assumed normal distributed and stationarity. GSTAR modelling for count data refers to the Time series model for count data, which are the Generalized Autoregressive Moving Average (GARMA) model and modeling Count Time Series which has the Generalized Linear Model (GLM) concept. The model formed is called the Poisson GSTAR model.