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R-optimal designs for trigonometric regression models

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Abstract

This paper is concerned with the problem of constructing R-optimal designs for trigonometric regression models with different orders. More precisely, explicit R-optimal designs for the first-order trigonometric regression model on a partial cycle are derived by using the idea of complete class approach. The relative R-efficiency of the equidistant sampling method is then discussed. Moreover, when the explanatory variable varies in a complete cycle, the R-optimal designs for estimating the specific pairs of the coefficients in the trigonometric regression of larger order are obtained by invoking the equivalence theorem. Several examples are presented for illustration.

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Authors and Affiliations

  1. Department of Mathematics, Shanghai Normal University, Shanghai, 200234, China

    Lei He & Rong-Xian Yue

  2. Scientific Computing Key Laboratory of Shanghai Universities, Shanghai, 200234, China

    Rong-Xian Yue

Authors
  1. Lei He
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  2. Rong-Xian Yue
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Corresponding author

Correspondence to Rong-Xian Yue.

Additional information

This work was supported by NSFC Grant 11471216

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He, L., Yue, RX. R-optimal designs for trigonometric regression models. Stat Papers 61, 1997–2013 (2020). https://doi.org/10.1007/s00362-018-1017-x

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  • DOI: https://doi.org/10.1007/s00362-018-1017-x

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