Parameter estimation for X-ray scattering analysis with Hamiltonian Markov Chain Monte Carlo
open access.
| Veröffentlicht in: | Journal of synchrotron radiation. - 1994. - 29(2022), Pt 3 vom: 01. Mai, Seite 721-731 |
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| 1. Verfasser: | |
| Weitere Verfasser: | , , , |
| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2022
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| Zugriff auf das übergeordnete Werk: | Journal of synchrotron radiation |
| Schlagworte: | Journal Article Markov chain Monte Carlo X-ray reflectivity small-angle X-ray scattering |
| Zusammenfassung: | open access. Bayesian-inference-based approaches, in particular the random-walk Markov Chain Monte Carlo (MCMC) method, have received much attention recently for X-ray scattering analysis. Hamiltonian MCMC, a state-of-the-art development in the field of MCMC, has become popular in recent years. It utilizes Hamiltonian dynamics for indirect but much more efficient drawings of the model parameters. We described the principle of the Hamiltonian MCMC for inversion problems in X-ray scattering analysis by estimating high-dimensional models for several motivating scenarios in small-angle X-ray scattering, reflectivity, and X-ray fluorescence holography. Hamiltonian MCMC with appropriate preconditioning can deliver superior performance over the random-walk MCMC, and thus can be used as an efficient tool for the statistical analysis of the parameter distributions, as well as model predictions and confidence analysis |
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| Beschreibung: | Date Revised 27.08.2024 published: Print-Electronic Citation Status PubMed-not-MEDLINE |
| ISSN: | 1600-5775 |
| DOI: | 10.1107/S1600577522003034 |