Abstract
A new class of simultaneous auto-models that clothe naturally the weak dependence of spatial processes, is presented. The parameters of the so-called auto-linear process are best linear prediction coefficients. With a finite transformation on the original process, the new process has auto-correlations equal to the parameters of interest. New method of moments estimators are proposed and they are consistent and asymptotically normal. Their variance matrix may be written down explicitly in terms of the auto-linear parameters and the result is distribution free. A simulation study and a data example are presented to support the use of the auto-linear model for spatial processes providing convenience for the statistical inference.
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Dimitriou-Fakalou, C. Statistical Inference for Spatial Auto-Linear Processes. J Stat Theory Pract 4, 345–365 (2010). https://doi.org/10.1080/15598608.2010.10411991
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DOI: https://doi.org/10.1080/15598608.2010.10411991