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Coffee-House Designs

  • Werner G. Müller
Chapter
Part of the Nonconvex Optimization and Its Applications book series (NOIA, volume 51)

Abstract

Designs that attempt to cover the experimental region as uniformly as possible, so called space-filling designs, have regained much interest after their successful linkage to D-optimum type designs by Johnson et al. (1990). The proposed maximin distance designs, however, are very difficult to generate, especially when the region is irregular or/and high dimensional and the number of design points is large.

(Coffee-house) Designs (see Müller, 1998) which are constructed by sequentially adding maximin distance points are asymptotically equivalent and reasonably efficient. A variant with good projective properties will be proposed and compared to the approach by Morris and Mitchell (1995). A relation to a design algorithm for random coefficient regression, cf. Fedorov and Müller (1989), is revealed.

Keywords

Space-filling designs spatial sampling Latin hypercubes 

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References

  1. Der Megréditchian, G. (1985). Methodes Statistiques d’Analyse et dInterpolation des Champs Meteorologiques. Geneve: Organisation Meteorologique Mondiale.Google Scholar
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Copyright information

© Springer Science+Business Media Dordrecht 2001

Authors and Affiliations

  • Werner G. Müller
    • 1
  1. 1.Department of StatisticsUniversity of Economics and Business AdministrationViennaAustria

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