A note on spatial–temporal lattice modeling and maximum likelihood estimation

Xiang Zhang and Yanbing Zheng

Statistics & Probability Letters, 2012, vol. 82, issue 12, 2145-2155

Abstract: Spatial–temporal linear models and the corresponding likelihood-based statistical inference are important tools for the analysis of spatial–temporal lattice data. In this paper, we study the asymptotic properties of maximum likelihood estimates under a general asymptotic framework for spatial–temporal linear models. We propose mild regularity conditions on the spatial–temporal weight matrices and derive the asymptotic properties (consistency and asymptotic normality) of maximum likelihood estimates. A simulation study is conducted to examine the finite-sample properties of the maximum likelihood estimates.

Keywords: Autoregressive models; Increasing domain asymptotics; Infill asymptotics; Linear regression; Spatial–temporal process (search for similar items in EconPapers)
Date: 2012
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DOI: 10.1016/j.spl.2012.07.019

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