Abstract
In this study, we derive the asymptotic normality of a class of rank estimators in a simple spatial linear regression model, when errors form a strongly mixing random field and when the spatial data are both on the lattice and on the irregularly spaced spatial sites. This result in turn is used to investigate the asymptotic relative efficiency (ARE) of these estimators relative to the LSE. In addition, we conduct numerical experiments under both the lattice and the irregularly spaced sampling, which lends support to the robustness of these estimators compared to the LSE.
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