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- W2097928305 abstract "A brief review of the literature on point estimators in linear calibration problems is undertaken. Supportive evidence for the relative merits of the classical and inverse regression models, drawn in general from the classical inferential and Bayesian approaches, is considered and the criteria for comparison of the estimators are discussed with respect to their suitability for certain classes of problems. the performance of the estimators is assessed with respect to determining the current value of ‘x’, the percentage concentration of administered drug levels in blood in this example. No single ‘best’ method of estimation appears to hold for all values of the unknown concentration when performance is assessed by criteria based on the mean square error (MSE). However, the inverse estimator would appear to be superior to the classical for those values of unknown X close to x." @default.
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- W2097928305 date "1989-06-01" @default.
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- W2097928305 title "Calibration: Regression models for concentration problems" @default.
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- W2097928305 doi "https://doi.org/10.1002/cem.1180030309" @default.
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