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Optimal extended complete block designs for dependent observations

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  • S. Pooladsaz
  • R. J. Martin

Abstract

Optimal designs under general dependence structures are usually difficult to specify theoretically or find algorithmically. However, they can sometimes be found for a specific dependence structure and a particular parameter value. In this paper, a class of generalized binary block designs with t treatments and b blocks of size k>t is considered. Each block consists of h consecutive complete blocks and, at the end, an incomplete block of size k−h t (if k > h t). For a suitable number of blocks, a universally optimal design is found for a first-order stationary autoregressive process with positive correlations. Optimal generalized binary designs and balanced block designs are also considered. Some constructions for a universally optimal design are described. A negative dependence parameter, and some other dependence structures, are also considered. Copyright Springer-Verlag 2005

Suggested Citation

  • S. Pooladsaz & R. J. Martin, 2005. "Optimal extended complete block designs for dependent observations," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 61(2), pages 185-197, April.
    • Handle: RePEc:spr:metrik:v:61:y:2005:i:2:p:185-197
    DOI: 10.1007/s001840400331
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    Cited by:

    1. Katarzyna Filipiak & Razieh Khodsiani & Augustyn Markiewicz, 2019. "Optimality of block designs under the model with the first-order circular autoregression," Statistical Papers, Springer, vol. 60(2), pages 427-447, April.
    2. Khodsiani, R. & Pooladsaz, S., 2017. "Universal optimal block designs under hub correlation structure," Statistics & Probability Letters, Elsevier, vol. 129(C), pages 387-392.
    3. Akram Fakhari-Esferizi & Saeid Pooladsaz, 2022. "Universally optimal balanced block designs for interference model," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 85(8), pages 1049-1061, November.

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