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DC poleHodnotaJazyk
dc.contributor.authorYang, Feng
dc.contributor.authorFu, Kuang
dc.contributor.authorZhou, Ai
dc.contributor.editorSkala, Václav
dc.date.accessioned2017-11-08T07:57:37Z
dc.date.available2017-11-08T07:57:37Z
dc.date.issued2014
dc.identifier.citationWSCG 2014: communication papers proceedings: 22nd International Conference in Central Europeon Computer Graphics, Visualization and Computer Visionin co-operation with EUROGRAPHICS Association, p. 205-211.en
dc.identifier.isbn978-80-86943-71-8
dc.identifier.uriwscg.zcu.cz/WSCG2014/!!_2014-WSCG-Communication.pdf
dc.identifier.urihttp://hdl.handle.net/11025/26416
dc.format7 s.cs
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherVáclav Skala - UNION Agencycs
dc.relation.ispartofseriesWSCG 2014: communication papers proceedingsen
dc.rights@ Václav Skala - UNION Agencycs
dc.subjectfMRI časové řadycs
dc.subjectklasická statistikacs
dc.subjectBayesovský závěrcs
dc.subjectskupinová analýzacs
dc.titleGroup analysis based on multilevel Bayesian for FMRI dataen
dc.typekonferenční příspěvekcs
dc.typeconferenceObjecten
dc.rights.accessopenAccessen
dc.type.versionpublishedVersionen
dc.description.abstract-translatedThis paper suggests one method to process fMRI time series based on Bayesian inference for group analysis. The method is based on Bayesian inference to divide group into multilevel by session, subject and group levels. It compares covariance to select prior to reinforce posterior probability in group analysis. At the same time it combines classical statistics, i.e., t-statistics to obtain voxel activation at subject level as prior for Bayesian inference at group level. Through the method, it can effectively decrease computation expensive and reduce complexity. Therefore the experimental results show robust on Bayesian inference for group analysis.en
dc.subject.translatedfMRI time seriesen
dc.subject.translatedclassical statisticsen
dc.subject.translatedBayesian inferenceen
dc.subject.translatedgroup analysisen
dc.type.statusPeer-revieweden
Vyskytuje se v kolekcích:WSCG 2014: Communication Papers Proceedings

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