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Spatial autoregression model: strong consistency

Let denote the Gauss-Newton estimator of the parameter ([alpha],[beta]) in the autoregression model Zij=[alpha]Zi-1,j+[beta]Zi,j-1-[alpha][beta]Zi-1,j-1+[var epsilon]ij. It is shown in an earlier paper that when converges in distribution to a bivariate normal random vector. A two-parameter strong martingale convergence theorem is employed here to prove that almost surely when .
Year of publication:
2003
Authors: Bhattacharyya, B. B. ; Ren, J. -J. ; Richardson, G. D. ; Zhang, J.
Published in:
Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 65.2003, 2, p. 71-77
Publisher: Elsevier
Keywords: Spatial autoregression Unit roots Two-parameter martingale
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Type of publication: Article
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Persistent link: https://www.econbiz.de/10005314059
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