A Weakly Informative Prior for Resonance Frequencies

Research output: Contribution to journalArticle

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 languageEnglish
Number of pages10
JournalPhysical Sciences Forum
Volume3
Issue number2
DOIs
Publication statusPublished - 4 Nov 2021
EventMAXENT 2021: 40th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering - Graz University of Technology, Graz, Austria
Duration: 4 Jul 20219 Jul 2021
https://www.tugraz.at/events/maxent2021/info/

Fingerprint

Dive into the research topics of 'A Weakly Informative Prior for Resonance Frequencies'. Together they form a unique fingerprint.

Cite this