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Biometrika Advance Access originally published online on November 6, 2008
Biometrika 2008 95(4):847-858; doi:10.1093/biomet/asn046
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© 2008 Biometrika Trust

Articles

Estimating equations for spatially correlated data in multi-dimensional space

Pei-Sheng Lin

Department of Mathematics, National Chung Cheng University, 168 University Road, Min-Hsiung, Chia-Yi 621, Taiwan
Division of Biostatistics and Bioinformatics, National Health Research Institutes, Miaoli 350, Taiwan pslin{at}math.ccu.edu.tw

Received for publication 1 June 2007. Revision received 1 May 2008.
  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 Lp 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.

Key Words: Asymptotic inference • Quasilikelihood estimating equation • Spatial data


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