Mean-Value Estimation with Validation Data
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Abstract
In this paper, the mean-value estimation problem with surrogate data and validation sampling is considered. A regression calibration kernel function is defined to incorporate the information contained in both surrogate variates and validation sampling. The proposed estimators are proved to be asymptotically normal and convergent rate.
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