Classical and Inverse Regression Methods of Calibration in Extrapolation

By R. Krutchkoff. 1969

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The Prediction Properties of Classical and Inverse Regression for the Simple Linear Calibration Problem (2010, methodology): “Krutchkoff (1967, 1969) compared classical calibration and inverse regression using Monte Carlo Journal of Quality Technology Vol. 42, No. 4, October 2010 simulation and recommended inverse regression based on the mean-squared error.”
The Prediction Properties of Inverse and Reverse Regression for the Simple Linear Calibration Problem (2010, methodology): “Krutchkoff (1967, 1969) compared inverse and reverse regression using Monte Carlo simulation and recommended reverse regression based on the mean squared error.”
Forecast calibration and combination: A simple Bayesian approach for ENSO (2004, background): “(14)], one can also think of defining the inverse regression model for u | and then use it directly for estimating ut. FollowingX this idea, Krutchkoff (1967, 1969), suggested the socalled inverse estimate: Kû 5 â 1 b̂Xt t (15) based on the least squares estimates â and b̂ obtained from the…”