The paper examines alternative estimators for the mean of a spatial process where observations are not independent. Properties of the sample mean and its standard error are contrasted with those of maximum likelihood estimators derived for three spatial models. The information loss caused by spatial dependency in the data is examined. The distribution theory for the estimators is reviewed and the paper concludes with an empirical example illustrating the properties of the estimators and the practical benefits of the maximum likelihood procedure.
No takes yet. Share an insight, caveat, or question.
Rober Haining (1988) studied this question.
Synapse has enriched 4 closely related papers on similar clinical questions. Consider them for comparative context: