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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.