Optimal multi-criteria designs for Fourier regression models

Peide Shi*, Kai-Tai Fang, Chih-Ling Tsai

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

4 Citations (Scopus)

Abstract

Riccomagno, Schwabe and Wynn (RSW) (1997) have given a necessary and sufficient condition for obtaining a complete Fourier regression model with a design based on lattice points that is D-optimal. However, in practice, the number of factors to be considered may be large, or the experimental data may be restricted or not homogeneous. To address these difficulties we extend the results of RSW to obtain a sufficient condition for an incomplete interaction Fourier model design based on lattice points that is D-, A-, E- and G-optimal. We also propose an algorithm for finding such optimal designs that requires fewer design points than those obtained using RSW's generators when the underlying model is a complete interaction model.

Original languageEnglish
Pages (from-to)387-401
Number of pages15
JournalJournal of Statistical Planning and Inference
Volume96
Issue number2
DOIs
Publication statusPublished - 1 Jul 2001
Externally publishedYes

Scopus Subject Areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty
  • Applied Mathematics

User-Defined Keywords

  • Fourier regression model
  • Lattice point
  • Optimal design

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