Antony M. Overstall
Abstract
Designs found by maximizing the expected Fisher information gain can result in a singular Fisher information matrix. This leads to non-unique classical estimates and ill-conditioning of posterior computation. A mitigating strategy for finding designs using Fisher information gain is proposed.
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Designs found by maximizing the expected Fisher information gain can result in a singular Fisher information matrix. This leads to non-unique classical estimates and ill-conditioning of posterior computation. A mitigating strategy for finding designs using Fisher information gain is proposed.
Key concepts: Fisher information, Information gain, Bayesian probability, Prior information, Computation, Bayes' theorem, Computer science, Mathematics