An insight into linear calibration: univariate case

Jason J. Z. Liao

Statistics & Probability Letters, 2002, vol. 56, issue 3, 271-281

Abstract: 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.

Keywords: Classical; estimator; Inverse; estimator; Weighted; least-squares; Optimal; weight; Mean; squared; error; (MSE); Integrated; MSE; (IMSE) (search for similar items in EconPapers)
Date: 2002
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