Lack-of-fit-efficiently optimal designs to estimate the highest coefficient of a polynomial with large degree

Wolfgang Bischoff and Frank Miller

Statistics & Probability Letters, 2006, vol. 76, issue 15, 1701-1704

Abstract: To check regression models Bischoff and Miller (2006a. Optimal designs which are efficient for lack of fit tests. Ann. Stat., to appear.) introduced optimal designs to estimate a parameter in the class of designs which guarantee a certain efficiency with respect to the power of a lack of fit (LOF-) test. One part of such an optimal design is absolutely continuous with respect to the Lebesgue measure and the other part consists of a finite number of mass points. The optimal design to estimate the highest coefficient of a polynomial regression of fixed degree k-1 (ek-optimal design) in the class of designs with LOF-efficiency of at least r has the same mass points as the classical ek-optimal design if r is small enough. In this paper we investigate the set of efficiencies r with that property.

Keywords: Polynomial; regression; model; Efficient; designs; for; lack; of; fit; tests; Efficient; ek-optimal; designs (search for similar items in EconPapers)
Date: 2006
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Citations: View citations in EconPapers (2)

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