DynamicOED.jl solves optimum experimental design problems, as it enables efficient parameter estimation from dynamic processes.
Optimum experimental design (OED) problems are typically encountered when unknown or uncertain parameters of mathematical models are to be estimated from an observable, maybe even controllable, process.In this scenario, OED can be used to decide on an experimental setup before collecting the data, i.e., deciding on when to measure and / or how to stimulate a dynamic process in order to maximize the amount of information gathered such that the parameters can be accurately estimated.
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Martensen et al. (2024) studied this question.
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