An insight into linear calibration: univariate case

In the linear controlled calibration literature, the classical least-squares estimator and the inverse estimator are the two main estimators. These two have different advantages and disadvantages. Investigation of these differences leads us to propose a class of weighted least-squares estimators that includes the classical, the inverse, and the orthogonal-regression approaches as special cases. Instead of pre-choosing the weight, a method is proposed to choose the optimal weight. An example is used to demonstrate the advantages of the new approach. (C) 2002 Elsevier Science B.V. All rights reserved.