Proper scoring rules : properties and applications

dc.contributor.advisorBickel, J. Eric
dc.contributor.committeeMemberHasenbein, John J
dc.contributor.committeeMemberLeibowicz, Benjamin D
dc.contributor.committeeMemberLandsberger, Sheldon
dc.creatorSmith, Zachary James
dc.creator.orcid0000-0001-5763-4432
dc.date.accessioned2021-06-12T05:22:01Z
dc.date.available2021-06-12T05:22:01Z
dc.date.created2019-12
dc.date.issued2020-03-27
dc.date.submittedDecember 2019
dc.date.updated2021-06-12T05:22:01Z
dc.description.abstractProper and strictly proper scoring rules provide a rigorous method for evaluating the accuracy of a probabilistic forecast while encouraging honesty. In this dissertation, we develop new proper and strictly proper scoring rules. We introduce additive and strongly additive scoring rules that can be used to reward a sequence of probabilistic forecasts. We construct new tailored scoring rules and demonstrate a general economic interpretation for all weighted proper scores. We also present a matrix-based construction method for scoring forecasts that can be represented as affine transformations of an underlying distribution.
dc.description.departmentOperations Research and Industrial Engineering
dc.format.mimetypeapplication/pdf
dc.identifier.urihttps://hdl.handle.net/2152/86466
dc.identifier.urihttp://dx.doi.org/10.26153/tsw/13417
dc.language.isoen
dc.subjectProper scoring rules
dc.subjectGeneralized entropy
dc.titleProper scoring rules : properties and applications
dc.typeThesis
dc.type.materialtext
thesis.degree.departmentOperations Research and Industrial Engineering
thesis.degree.disciplineOperations Research and Industrial Engineering
thesis.degree.grantorThe University of Texas at Austin
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy
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