Publication:
Higher order asymptotic computation of Bayesian significance tests for precise none hypotheses in the presence of nuisance parameters

Simple item page
dc.affiliation.dptoUC3M. Departamento de Estadísticaes
dc.contributor.authorCabras, Stefano
dc.contributor.authorRacugno, Walter
dc.contributor.authorVentura, Laura
dc.contributor.funderMinisterio de Economía y Competitividad (España)es
dc.date.accessioned2022-06-22T14:32:04Z
dc.date.available2022-06-22T14:32:04Z
dc.date.issued2015-10-13
dc.description.abstractThe full Bayesian significance test (FBST) was introduced by Pereira and Stern for measuring the evidence of a precise none hypothesis. The FBST requires both numerical optimization and multidimensional integration, whose computational cost may be heavy when testing a precise none hypothesis on a scalar parameter of interest in the presence of a large number of nuisance parameters. In this paper we propose a higher order approximation of the measure of evidence for the FBST, based on tail area expansions of the marginal posterior of the parameter of interest. When in particular focus is on matching priors, further results are highlighted. Numerical illustrations are discussed.en
dc.description.sponsorshipThis work was supported the Cariparo Foundation Excellence grant 2011/2012, and by grants from Regione Autonoma della Sardegna (CRP-59903) and Ministerio de Economia y Competitividad of Spain (ECO2012-38442, RYC-2012- 11455).en
dc.identifier.bibliographicCitationCabras, S., Racugno, W., & Ventura, L. (2014). Higher order asymptotic computation of Bayesian significance tests for precise null hypotheses in the presence of nuisance parameters. Journal of Statistical Computation and Simulation, 85 (15), pp. 2989-3001.es
dc.identifier.doihttps://doi.org/10.1080/00949655.2014.947288
dc.identifier.issn0094-9655
dc.identifier.publicationfirstpage2989es
dc.identifier.publicationissue15es
dc.identifier.publicationlastpage3001es
dc.identifier.publicationtitleJOURNAL OF STATISTICAL COMPUTATION AND SIMULATIONen
dc.identifier.publicationvolume85es
dc.identifier.urihttps://hdl.handle.net/10016/35235
dc.identifier.uxxiAR/0000017122
dc.language.isoenges
dc.publisherTaylor & Francises
dc.relation.projectIDGobierno de España. ECO2012-38442es
dc.relation.projectIDGobierno de España. RYC-2012-11455es
dc.rights© 2014 Taylor & Francises
dc.rightsAtribución-NoComercial 3.0 España*
dc.rights.accessRightsopen accessen
dc.rights.urihttp://creativecommons.org/licenses/by-nc/3.0/es/*
dc.subject.ecienciaEstadísticaes
dc.subject.otherEvidenceen
dc.subject.otherHighest probability density seten
dc.subject.otherHOTA algorithmen
dc.subject.otherMatching priorsen
dc.subject.otherPereira and Stern procedureen
dc.subject.otherProfile and modified profile likelihood rooten
dc.subject.otherTail area approximationen
dc.titleHigher order asymptotic computation of Bayesian significance tests for precise none hypotheses in the presence of nuisance parametersen
dc.typeresearch article*
dc.type.hasVersionAM*
dspace.entity.typePublication
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
higher_JSCS_2015_ps.pdf
Size:
1.36 MB
Format:
Adobe Portable Document Format
Download
Collections
DES - Artículos de Revistas