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Maximum-Entropy Priors with Derived Parameters in a Specified Distribution
We propose a method for transforming probability distributions so that parameters of interest are forced into a specified distribution. We prove that this approach is the maximum-entropy choice, and provide a motivating example, applicable to neutrino-hierarchy inference.
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2019
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7514752/ https://www.ncbi.nlm.nih.gov/pubmed/33266987 http://dx.doi.org/10.3390/e21030272 |