The search for an organizing physical framework for statistics

dc.contributor.advisorWiggins, Paul A
dc.contributor.authorLaMont, Colin
dc.date.accessioned2018-07-31T21:17:03Z
dc.date.available2018-07-31T21:17:03Z
dc.date.issued2018-07-31
dc.date.submitted2018
dc.descriptionThesis (Ph.D.)--University of Washington, 2018
dc.description.abstractTheories 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.termsOpen Access
dc.format.mimetypeapplication/pdf
dc.identifier.otherLaMont_washington_0250E_18701.pdf
dc.identifier.urihttp://hdl.handle.net/1773/42512
dc.language.isoen_US
dc.rightsCC BY
dc.subjectBayesian
dc.subjectFrequentist
dc.subjectInformation Criteria
dc.subjectModel Selection
dc.subjectStatistical Mechanics
dc.subjectThermodynamics
dc.subjectStatistical physics
dc.subjectStatistics
dc.subject.otherPhysics
dc.titleThe search for an organizing physical framework for statistics
dc.typeThesis

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