Abstract

A method is proposed for designing nonlinear univariate calibration of measuring instruments. The problem addressed is how to select a set of design points (standards or calibrators) to minimize the errors in the inverse predictions. The Curve parameters are assumed to vary randomly between calibrations, with known expected value and known covariance matrix. A design criterion is suggested for analytical procedures, according to which the coefficient of variation and the area under the precision profile are minimized.

Keywords

Dose-response; Four-parameter logistic function; Inverse prediction; Michaelis-Menten function; Nonlinear regression; Optimal design

Published in

Technometrics
2008, volume: 50, number: 4, pages: 479-486
Publisher: American Statistical Association

Authors' information