A Three-Stage Iterative Procedure for Space-Time Modeling

Phillip E. Pfeifer · Stuart Jay Deutsch

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Spatial and Panel Data Analysis Time Series Analysis and Forecasting Statistical and numerical algorithms

Abstract

A three-stage iterative procedure for building space-time models is presented. These models fall into the general class of STARIMA models and are characterized by autoregressive and moving average terms lagged in both time and space. This model class collapses into the ARIMA model class in the absence of spatial correlation. The theoretical properties of STARIMA models are presented and the model building procedure is described and illustrated by a substantive example.

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1977Time Series Analysis: Forecasting and Control 1974Spatial Interaction and the Statistical Analysis of Lattice Systems 2000Forecasting Economic Time Series

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2001Dynamic Models in Space and Time 2010On vector autoregressive modeling in space and time 2004Unconditional Maximum Likelihood Estimation of Linear and Log‐Linear Dynamic Models for Spatial Panels 2003Aggregation of space-time processes 2011Spatio-temporal autocorrelation of road network data 2000Blur-generated non-separable space–time models 1980Identification and Interpretation of First Order Space-Time ARMA Models 2007Spatial Vector Autoregressions

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