Gauss-Newton Estimation Of Parameters For A Spatial Autoregression Model

    Authors

    B. B. Bhattacharyya; T. M. Khalil;G. D. Richardson

    Comments

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    Abbreviated Journal Title

    Stat. Probab. Lett.

    Keywords

    martingale central limit theorem; spatial autoregression; unit root; estimation; CENTRAL LIMIT THEOREMS; Statistics & Probability

    Abstract

    Estimation of (alpha,beta)' in the doubly geometric model Z(ij) = alpha Z(i-1,j) + beta Z(i,j-1) - alpha beta Z(i-1,j-1) + epsilon(ij) is discussed for the cases (i) alpha = 1, \B\ < 1 and(ii) alpha = beta = 1. In each case, the ''one step Gauss-Newton estimator'' is shown, when properly normalized, to be asymptotically normal.

    Journal Title

    Statistics & Probability Letters

    Volume

    28

    Issue/Number

    2

    Publication Date

    1-1-1996

    Document Type

    Article

    Language

    English

    First Page

    173

    Last Page

    179

    WOS Identifier

    WOS:A1996UN68600014

    ISSN

    0167-7152

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