An insight into linear calibration: univariate case
AbstractIn 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.
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Bibliographic InfoArticle provided by Elsevier in its journal Statistics & Probability Letters.
Volume (Year): 56 (2002)
Issue (Month): 3 (February)
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Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description
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- Kubokawa, T. & Robert, C. P., 1994. "New Perspectives on Linear Calibration," Journal of Multivariate Analysis, Elsevier, vol. 51(1), pages 178-200, October.
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