Stochastic Distance Optimality
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.
KeywordsInformation Matrix Coverage Probability Distance Optimality Less Square Estimator Hadamard Matrix
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