Optimal and robust designs for trigonometric regression models

Xiaojian Xu () and Xiaoli Shang ()

Metrika: International Journal for Theoretical and Applied Statistics, 2014, vol. 77, issue 6, 753-769

Abstract: This article presents discussions on the optimal and robust designs for trigonometric regression models under different optimality criteria. First, we investigate the classical Q-optimal designs for estimating the response function in a full trigonometric regression model with a given order. The equivalencies of Q-, A-, and G-optimal designs for trigonometric regression in general are also articulated. Second, we study minimax designs and their implementation in the case of trigonometric approximation under Q-, A-, and D-optimality. Then, We indicate the existence of the symmetric designs that are D-optimal minimax designs for general trigonometric regression models, and prove the existence of the symmetric designs that are Q- or A-optimal minimax designs for two particular trigonometric regression models under certain conditions. Copyright Springer-Verlag Berlin Heidelberg 2014

Keywords: Fourier regression; Symmetric design; Uniform design; Least squares estimation; Expected mean squared errors (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s00184-013-0463-7

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