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Measures for designs in experiments with correlated errors

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  • Werner G. Müller

Abstract

In this paper we consider optimal design of experiments in the case of correlated observations. We use and further develop the concept of design measures introduced by Pázman & Müller (1998) for the construction of a simple, quick and elegant design algorithm. We support the construction of this algorithm for a general correlation structure by an interpretation in terms of norms. Examples demonstrate that our results are useful for generating exact designs by sampling from the obtained design measures. Copyright Biometrika Trust 2003, Oxford University Press.

Suggested Citation

  • Werner G. Müller, 2003. "Measures for designs in experiments with correlated errors," Biometrika, Biometrika Trust, vol. 90(2), pages 423-434, June.
  • Handle: RePEc:oup:biomet:v:90:y:2003:i:2:p:423-434
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    Cited by:

    1. Radoslav Harman & František Štulajter, 2010. "Optimal prediction designs in finite discrete spectrum linear regression models," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 72(2), pages 281-294, September.
    2. Milan Stehlík & Juan Rodríguez-Díaz & Werner Müller & Jesús López-Fidalgo, 2008. "Optimal allocation of bioassays in the case of parametrized covariance functions: an application to Lung’s retention of radioactive particles," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 17(1), pages 56-68, May.

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