A variance estimator for the mean of a systematic sample in two dimensions is proposed and analyzed. The estimation strategy relies on a super-population model which follows a spatial auto-regressive structure and allows for the presence of covariates. The small sample properties of the proposed procedure are analyzed by simulations: the model-based estimation strategy shows an excellent performance in a variety of situations which are common in real situations.
Model-based variance estimation in two-dimensional systematic sampling
Santi, Flavio;
2017-01-01
Abstract
A variance estimator for the mean of a systematic sample in two dimensions is proposed and analyzed. The estimation strategy relies on a super-population model which follows a spatial auto-regressive structure and allows for the presence of covariates. The small sample properties of the proposed procedure are analyzed by simulations: the model-based estimation strategy shows an excellent performance in a variety of situations which are common in real situations.
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