Abstract
For spatial regressions with sinusoidal surfaces, the ordinary least squares estimator (OLSE) is shown to be asymptotically as efficient as the geeralized least squares estimator (GLSE) in that the covariance matrices of the two estimators have the same nontrivial limit under the same normalization.
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This research was supported by a grant from Ewha University
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Shin, D.W., Kim, DG. & Kim, H.J. Efficiency of the OLSE for regressions on two-dimensional grids with sinusoidal regressors and spatially correlated errors. Metrika 56, 247–258 (2002). https://doi.org/10.1007/s001840100177
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DOI: https://doi.org/10.1007/s001840100177