Model-assisted sample design is minimax for model-based prediction
Probability sampling designs are sometimes used in conjunction with model-based predictors of finite population quantities. These designs should minimize the anticipated variance (AV), which is the variance over both the superpopulation and sampling processes, of the predictor of interest. The AV-optimal design is well known for model-assisted estimators which attain the Godambe-Joshi lower bound for the AV of design-unbiased estimators. However, no optimal probability designs have been found...[Show more]
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