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Robustness properties of A-, D-, and E-optimal designs for polynomial growth models with autocorrelated errors

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  • Moerbeek, M.

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  • Moerbeek, M., 2005. "Robustness properties of A-, D-, and E-optimal designs for polynomial growth models with autocorrelated errors," Computational Statistics & Data Analysis, Elsevier, vol. 48(4), pages 765-778, April.
    • Handle: RePEc:eee:csdana:v:48:y:2005:i:4:p:765-778
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    References listed on IDEAS

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    1. Wong, Weng Kee, 1994. "Comparing robust properties of A, D, E and G-optimal designs," Computational Statistics & Data Analysis, Elsevier, vol. 18(4), pages 441-448, November.
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    Cited by:

    1. J. López Fidalgo & I. M. Ortiz Rodr�guez & Weng Kee Wong, 2011. "Design issues for population growth models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(3), pages 501-512, November.
    2. Candel, Math J.J.M. & Van Breukelen, Gerard J.P., 2010. "D-optimality of unequal versus equal cluster sizes for mixed effects linear regression analysis of randomized trials with clusters in one treatment arm," Computational Statistics & Data Analysis, Elsevier, vol. 54(8), pages 1906-1920, August.
    3. Anna Szczepańska, 2013. "Simultaneous choice of time points and the block design in the growth curve model," Statistical Papers, Springer, vol. 54(2), pages 413-425, May.
    4. Víctor Casero-Alonso & Andrey Pepelyshev & Weng K. Wong, 2018. "A web-based tool for designing experimental studies to detect hormesis and estimate the threshold dose," Statistical Papers, Springer, vol. 59(4), pages 1307-1324, December.
    5. I. Ortiz & I. Martínez & C. Rodríguez & Y. Águila, 2009. "Optimal designs for generalized linear models with biased response," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 70(2), pages 225-237, September.

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    1. J. López Fidalgo & I. M. Ortiz Rodr�guez & Weng Kee Wong, 2011. "Design issues for population growth models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(3), pages 501-512, November.
    2. Víctor Casero-Alonso & Andrey Pepelyshev & Weng K. Wong, 2018. "A web-based tool for designing experimental studies to detect hormesis and estimate the threshold dose," Statistical Papers, Springer, vol. 59(4), pages 1307-1324, December.
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