Abstract
We derive a weakly informative prior for a set of ordered resonance frequencies from Jaynes’ principle of maximum entropy. The prior facilitates model selection problems in which both the number and the values of the resonance frequencies are unknown. It encodes a weakly inductive bias, provides a reasonable density everywhere, is easily parametrizable, and is easy to sample. We hope that this prior can enable the use of robust evidence-based methods for a new class of problems, even in the presence of multiplets of arbitrary order.
Original language | English |
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Number of pages | 10 |
Journal | Physical Sciences Forum |
Volume | 3 |
Issue number | 2 |
DOIs | |
Publication status | Published - 4 Nov 2021 |
Event | MAXENT 2021: 40th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering - Graz University of Technology, Graz, Austria Duration: 4 Jul 2021 → 9 Jul 2021 https://www.tugraz.at/events/maxent2021/info/ |