The search for an organizing physical framework for statistics
| dc.contributor.advisor | Wiggins, Paul A | |
| dc.contributor.author | LaMont, Colin | |
| dc.date.accessioned | 2018-07-31T21:17:03Z | |
| dc.date.available | 2018-07-31T21:17:03Z | |
| dc.date.issued | 2018-07-31 | |
| dc.date.submitted | 2018 | |
| dc.description | Thesis (Ph.D.)--University of Washington, 2018 | |
| dc.description.abstract | Theories of statistical analysis remain in conflict and contradiction. But nature reveals an elegant and coherent formulation of statistics in the thermal properties of physical systems. Demanding that a viable statistical theory share the properties of a viable physical theory---observer independence and coordinate invariance---resolves outstanding controversies in statistical model selection. Furthermore, by using constructions taken directly from thermodynamics, a predictive approach to model selection can be reconciled with a Bayesian approach to parameter uncertainty. This approach also solves the longstanding problem of the undetermined Bayesian prior. | |
| dc.embargo.terms | Open Access | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.other | LaMont_washington_0250E_18701.pdf | |
| dc.identifier.uri | http://hdl.handle.net/1773/42512 | |
| dc.language.iso | en_US | |
| dc.rights | CC BY | |
| dc.subject | Bayesian | |
| dc.subject | Frequentist | |
| dc.subject | Information Criteria | |
| dc.subject | Model Selection | |
| dc.subject | Statistical Mechanics | |
| dc.subject | Thermodynamics | |
| dc.subject | Statistical physics | |
| dc.subject | Statistics | |
| dc.subject.other | Physics | |
| dc.title | The search for an organizing physical framework for statistics | |
| dc.type | Thesis |
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