Optimal Design for Compositional Data

  • Roelof L. J. Coetzer
  • Linda M. Haines
Conference paper
Part of the Contributions to Statistics book series (CONTRIB.STAT.)


In this paper optimal designs for experiments involving compositional data, specifically locally D-optimal designs for the additive logistic normal model and locally D S -optimal designs for Dirichlet regression, are investigated. The theory underpinning the construction of these designs is based on the appropriate information matrices and the development, while new, is relatively straightforward. The ideas are illustrated by means of a simple example, that of two consecutive reactions.


Optimal Design Design Space Information Matrix Compositional Data Consecutive Reaction 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Linda Haines would like to thank the University of Cape Town, the National Research Foundation and SASOL, South Africa, for financial support.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  1. 1.Sasol TechnologySasolburgSouth Africa
  2. 2.Department of Statistical SciencesUniversity of Cape TownRondeboschSouth Africa

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