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Explicit T-optimal Designs for Trigonometric Regression Models

  • Viatcheslav B. Melas
  • Petr V. Shpilev
Conference paper
Part of the Springer Proceedings in Mathematics & Statistics book series (PROMS, volume 231)

Abstract

This chapter devotes to the problem of constructing T-optimal discriminating designs for Fourier regression models which differ by at most three trigonometric functions. Here we develop the results obtained in a paper (Dette, Melas and Shpilev (2015). T-optimal discriminating designs for Fourier regression models. 1–17) [11] and give a few its generalizations. We consider in detail the case of discriminating between two models where the order of the larger one equals two. For this case, we provide explicit solutions and investigate the dependence of the locally T-optimal discriminating designs on the parameters of the larger model. The results obtained in the chapter can also be applied in classical approximation theory.

Keywords

T-optimal design Model discrimination Linear optimality criteria Trigonometric models 

Notes

Acknowledgements

The authors would like to thank Lyudmila Kuznetsova, who helped improving the text of this manuscript with considerable language expertise. This work has been supported by St. Petersburg State University (project “Actual problems of design and analysis for regression models,” 6.38.435.2015) and by Russian Foundation for Basic Research (project no. 17-01-00161-a).

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of MathematicsSt. Petersburg State UniversitySt. PetersburgRussia

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