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D-optimal chemical balance weighing designs with autoregressive errors

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  • Krystyna Katulska
  • Łukasz Smaga

Abstract

In this paper, we consider the estimation problem of individual weights of three objects. For the estimation we use the chemical balance weighing design and the criterion of D-optimality. We assume that the error terms $${\varepsilon_{i},\ i=1,2,\dots,n,}$$ are a first-order autoregressive process. This assumption implies that the covariance matrix of errors depends on the known parameter ρ. We present the chemical balance weighing design matrix $${\widetilde{\bf X}}$$ and we prove that this design is D-optimal in certain classes of designs for $${\rho\in[0,1)}$$ and it is also D-optimal in the class of designs with the design matrix $${{\bf X} \in M_{n\times 3}(\pm 1)}$$ for some ρ ≥ 0. We prove also the necessary and sufficient conditions under which the design is D-optimal in the class of designs $${M_{n\times 3}(\pm 1)}$$ , if $${\rho\in[0,1/(n-2))}$$ . We present also the matrix of the D-optimal factorial design with 3 two-level factors. Copyright The Author(s) 2013

Suggested Citation

  • Krystyna Katulska & Łukasz Smaga, 2013. "D-optimal chemical balance weighing designs with autoregressive errors," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 76(3), pages 393-407, April.
  • Handle: RePEc:spr:metrik:v:76:y:2013:i:3:p:393-407
    DOI: 10.1007/s00184-012-0394-8
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    References listed on IDEAS

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    1. Hong-Gwa Yeh & Mong-Na Lo Huang, 2005. "On exact D-optimal designs with 2 two-level factors and n autocorrelated observations," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 61(3), pages 261-275, June.
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    Cited by:

    1. Łukasz Smaga, 2016. "A note on D-optimal chemical balance weighing designs with autocorrelated observations," Statistical Papers, Springer, vol. 57(3), pages 721-730, September.

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    1. Łukasz Smaga, 2016. "A note on D-optimal chemical balance weighing designs with autocorrelated observations," Statistical Papers, Springer, vol. 57(3), pages 721-730, September.

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