Journal of Statistical Theory and Practice

, Volume 7, Issue 4, pp 658–673 | Cite as

Optimal Designs for Regression Models With a Constant Coefficient of Variation

  • Holger Dette
  • Werner G. MüllerEmail author


In this article we consider the problem of constructing optimal designs for models with a constant coefficient of variation. We explore the special structure of the information matrix in these models and derive a characterization of optimal designs in the sense of Kiefer and Wolfowitz (1960). Besides locally optimal designs, Bayesian and standardized minimax optimal designs are also considered. Particular attention is spent on the problem of constructing D-optimal designs. The results are illustrated in several examples where optimal designs are calculated analytically and numerically.


Optimal design Heteroscedasticity Constant coefficient of variation Polynomial regression 

AMS Subject Classification



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© Grace Scientific Publishing 2013

Authors and Affiliations

  1. 1.Fakultät für MathematikRuhr-Universität BochumBochumGermany
  2. 2.Institut für Angewandte StatistikJohannes Kepler Universität LinzLinzAustria

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