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TSLiNGAM: DirectLiNGAM Under Heavy Tails

 
dc.contributor.authorLeyder, Sarah
dc.contributor.authorRaymaekers, Jakob
dc.contributor.authorVerdonck, Tim
dc.contributor.imecauthorVerdonck, Tim
dc.contributor.orcidimecVerdonck, Tim::0000-0003-1105-2028
dc.date.accessioned2025-07-09T12:35:03Z
dc.date.available2024-10-05T18:00:19Z
dc.date.available2025-07-09T12:35:03Z
dc.date.issued2025
dc.description.wosFundingTextSL was supported by Fonds Wetenschappelijk onderzoek - Vlaanderen (FWO) as a PhD fellow Fundamental Research (PhD fellowship 11K5523N). JR was supported by the European Union's Horizon 2022 research and innovation program under the Marie Sklodowska Curiegrant agreement No 101103017. This research also received funding fromthe Flemish Government under the "Onderzoeksprogramma ArtificieleIntelligentie (AI) Vlaanderen" programme.
dc.identifier.doi10.1080/10618600.2024.2394462
dc.identifier.issn1061-8600
dc.identifier.urihttps://imec-publications.be/handle/20.500.12860/44604
dc.publisherTAYLOR & FRANCIS INC
dc.source.beginpage437
dc.source.endpage447
dc.source.issue2
dc.source.journalJOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS
dc.source.numberofpages11
dc.source.volume34
dc.subject.keywordsGAUSSIAN ACYCLIC MODEL
dc.subject.keywordsCAUSAL DISCOVERY
dc.subject.keywordsREGRESSION
dc.subject.keywordsROBUST
dc.subject.keywordsSIMULATION
dc.subject.keywordsESTIMATOR
dc.subject.keywordsALGORITHM
dc.title

TSLiNGAM: DirectLiNGAM Under Heavy Tails

dc.typeJournal article
dspace.entity.typePublication
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