Abstract
Model(s): Discrete design models and regression models Experimental domains: Binary design set-up and T = [0, 1] and [−1,1] for continuous regressors Optimality criteria: Maximization of distance optimality functional Major tools: Probability inequalities, Schur convexity, invariance Optimality results: Optimal regression designs, optimal designs under CRD and BIBD set-up Thrust: Non-standard optimality functional, normality of error distribution This Chapter addresses optimality issues for a non-standard optimality criterion viz., the distance optimality criterion-originally introduced in Sinha (1970). Both discrete and regression design models are studied and specific optimality results are presented. This criterion has gained momentum only recently.
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Liski, E.P., Mandal, N.K., Shah, K.R., Sinha, B.K. (2002). Stochastic Distance Optimality. 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_5
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DOI: https://doi.org/10.1007/978-1-4613-0049-6_5
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