Workshop in Model-Oriented Design and Analysis
نویسندگان
چکیده
Among optimality criteria adopted to select best experimental designs to discriminate between different models, the KL-optimality criterion is very general. A KL-optimum design is obtained from a minimax optimization problem on an infinite-dimensional space. In this paper some important properties of the KL-optimality criterion function are highlighted and an algorithm to construct a KL-optimum design is proposed. It is analytically proved that a sequence of designs obtained by iteratively applying this algorithm converges to the set of KL-optimum designs, provided that the designs are regular. Furthermore a regularization procedure is discussed.
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