Title

Spatial autoregression model: strong consistency

Authors

Authors

B. B. Bhattacharyya; J. J. Ren; G. D. Richardson;J. Zhang

Comments

Authors: contact us about adding a copy of your work at STARS@ucf.edu

Abbreviated Journal Title

Stat. Probab. Lett.

Keywords

spatial autoregression; unit roots; two-parameter martingale; Statistics & Probability

Abstract

Let (alpha(n), beta(n)) denote the Gauss-Newton estimator of the parameter (alpha, beta) in the autoregression model Z(ij) = alphaZ(i-1,j) + betaZ(i,j-1) - alphabetaZ(i-1),(j-1) + epsilon(ij). It is shown in an earlier paper that when alpha = beta = 1, {n(3/2)(alpha(n)-alpha, beta(n)-beta)} converges in distribution to a bivariate normal random vector. A two-parameter strong martingale convergence theorem is employed here to prove that n(r)(alpha(n)-alpha, beta(n)-beta) -- > (0) under bar almost surely when r < (3)/(2). (C) 2003 Published by Elsevier B.V.

Journal Title

Statistics & Probability Letters

Volume

65

Issue/Number

2

Publication Date

1-1-2003

Document Type

Article

Language

English

First Page

71

Last Page

77

WOS Identifier

WOS:000186624200001

ISSN

0167-7152

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