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On maximin designs for correlated observations

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  • Bischoff, Wolfgang

Abstract

In the linear model, we consider the problem of finding optimal or efficient designs with respect to the D-criterion when the covariance matrix is an unknown element of a class . In general, designs that are efficient for each do not exist. Therefore, maximin designs are of interest. These designs maximize the minimal efficiency where the minimum is taken over all possible covariance matrices and the maximum is taken over all feasible designs. Efficient maximin designs are derived for tridiagonal covariance matrices.

Suggested Citation

  • Bischoff, Wolfgang, 1996. "On maximin designs for correlated observations," Statistics & Probability Letters, Elsevier, vol. 26(4), pages 357-363, March.
    • Handle: RePEc:eee:stapro:v:26:y:1996:i:4:p:357-363
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    References listed on IDEAS

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    1. Wolfgang Bischoff, 1995. "Determinant formulas with applications to designing when the observations are correlated," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 47(2), pages 385-399, June.
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    Cited by:

    1. Das, Rabindra Nath & Kim, Jinseog & Park, Jeong-Soo, 2015. "Robust D-optimal designs under correlated error, applicable invariantly for some lifetime distributions," Reliability Engineering and System Safety, Elsevier, vol. 136(C), pages 92-100.

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