Nonparametric Survey Regression Estimation in Two-Stage Spatial Sampling
نویسندگان
چکیده
A nonparametric model-assisted survey estimator for status estimation based on local polynomial regression is extended to incorporate spatial auxiliary information. Under mild assumptions, this estimator is design-unbiased and consistent. Simulation studies show that the nonparametric regression estimator is competitive with standard parametric techniques when a parametric specification is correct, and outperforms those techniques when the parametric specification is incorrect. The methodology is applied to water chemistry data from the EMAP Northeastern Lakes Survey.
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