Estimating equations for spatially correlated data in multi-dimensional space

Pei-Sheng Lin

Biometrika, 2008, vol. 95, issue 4, 847-858

Abstract: We use the quasilikelihood concept to propose an estimating equation for spatial data with correlation across the study region in a multi-dimensional space. With appropriate mixing conditions, we develop a central limit theorem for a random field under various L p metrics. The consistency and asymptotic normality of quasilikelihood estimators can then be derived. We also conduct simulations to evaluate the performance of the proposed estimating equation, and a dataset from East Lansing Woods is used to illustrate the method. Copyright 2008, Oxford University Press.

Date: 2008
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