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Optimal confidence intervals for the geometric parameter

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dc.contributor.authorYang, Mo
dc.contributor.authorPuza, Borek
dc.date.accessioned2023-06-27T23:12:23Z
dc.date.issued2019
dc.date.updated2022-04-03T08:22:19Z
dc.description.abstractThis article discusses optimal confidence estimation for the geometric parameter and shows how different criteria can be used for evaluating confidence sets within the framework of tail functions theory. The confidence interval obtained using a particular tail function is studied and shown to outperform others, in the sense of having smaller width or expected width under a specified weight function. It is also shown that it may not be possible to find the most powerful test regarding the parameter using the Neyman-Pearson lemma. The theory is illustrated by application to a fecundability study.en_AU
dc.description.sponsorshipMo Yang was partially supported by Research Grant 101/130028852 from the Key Laboratory forApplied Statistics of MOE, Northeast Normal University, Changchun, China, and Research GrantDUFE2017Q03 from Dongbei University of Finance and Economics, Dalian, Chinaen_AU
dc.format.mimetypeapplication/pdfen_AU
dc.identifier.issn0361-0926en_AU
dc.identifier.urihttp://hdl.handle.net/1885/293741
dc.language.isoen_AUen_AU
dc.publisherTaylor & Francis Groupen_AU
dc.rights© 2019 Taylor & Francis Group, LLCen_AU
dc.sourceCommunications in Statistics: Theory and Methodsen_AU
dc.subjectGeometric parameteren_AU
dc.subjectoptimal interval estimationen_AU
dc.subjecttail functionen_AU
dc.subjectpriorexpected widthen_AU
dc.titleOptimal confidence intervals for the geometric parameteren_AU
dc.typeJournal articleen_AU
local.bibliographicCitation.issue3en_AU
local.bibliographicCitation.lastpage606en_AU
local.bibliographicCitation.startpage590en_AU
local.contributor.affiliationYang, Mo, Dongbei University of Finance and Economicsen_AU
local.contributor.affiliationPuza, Borek, College of Business and Economics, ANUen_AU
local.contributor.authoruidPuza, Borek, u9303975en_AU
local.description.embargo2099-12-31
local.description.notesImported from ARIESen_AU
local.identifier.absfor490509 - Statistical theoryen_AU
local.identifier.absfor490599 - Statistics not elsewhere classifieden_AU
local.identifier.ariespublicationu6269649xPUB598en_AU
local.identifier.citationvolume49en_AU
local.identifier.doi10.1080/03610926.2018.1549242en_AU
local.identifier.scopusID2-s2.0-85062783984
local.publisher.urlhttps://www.tandfonline.com/en_AU
local.type.statusPublished Versionen_AU

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