Abstract
Model(s): Fixed coefficients regression (FCR), random coefficients regression (RCR) models (single factor linear, quadratic and cubic) Experimental domains: [0, 1], [0, h] and (h, H] Optimality criteria: Minimization of optimality functionals Major tools: de la Garza (DLG) phenomenon and Loewner order domination (LOD) of information matrices for search reduction Optimality results: Specific optimal designs under regression models for estimation, prediction and inverse prediction — all under continuous design theory Thrust: Asymmetric experimental domains
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Liski, E.P., Mandal, N.K., Shah, K.R., Sinha, B.K. (2002). Optimal Regression Designs in Asymmetric Domains. In: Topics in Optimal Design. Lecture Notes in Statistics, vol 163. Springer, New York, NY. https://doi.org/10.1007/978-1-4613-0049-6_3
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DOI: https://doi.org/10.1007/978-1-4613-0049-6_3
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