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Large-sample comparisons of calibration procedures when both measurements are subject to error: the unreplicated case
Authors:Seung-Hoon Lee  Bong-Jin Yum
Affiliation:Department of Industrial Engineering , Korea Advanced Institute of Science and Technology , P.O.Box 150, Chongryang, Seoul, Korea
Abstract:A predictive functional relationship model is presented for the calibration problem in which the standard as well as the nonstandard measurements are subject to error. For the estimation of the relationship between the two measurements, the ordinary least squares and maximum likelihood estimation methods are considered, while for the prediction of unknown standard measurements we consider direct and inverse approaches. Relative performances of those calibration procedures are compared in terms of the asymptotic mean square error of prediction.
Keywords:errons-in-varialles model  functional relationship  ordinary least square estimation  maximum likelihood estimation  direct prediction  inverse prediction
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