Comparing robust properties of A, D, E and G-optimal designs
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Cited by:
- Eugene C. Ukaegbu & Polycarp E. Chigbu, 2017. "Evaluation of Orthogonally Blocked Central Composite Designs with Partial Replications," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 79(1), pages 112-141, May.
- 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.
- 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.
- 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.
- Dette, Holger & Franke, Tobias, 2000. "Robust designs for polynomial regression by maximizing a minimum of D- and D1-efficiencies," Technical Reports 2000,38, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
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