Typical optimal design methods for inverse or parameter estimation problems are designed to choose optimal sampling distributions through minimization of a specific cost function related to the resulting error in parameter estimates. It is hoped that the inverse problem will produce parameter estimates with increased accuracy using data from the optimal sampling distribution. We present a new Prohorov metric based theoretical framework that permits one to treat succinctly and rigorously ...
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