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Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/235556
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dc.titleThe G-Wishart Weighted Proposal Algorithm: Efficient Posterior Computation for Gaussian Graphical Models
dc.contributor.authorWillem van den Boom
dc.contributor.authorAlexandros Beskos
dc.contributor.authorMaria De Iorio
dc.date.accessioned2022-12-14T02:26:13Z
dc.date.available2022-12-14T02:26:13Z
dc.date.issued2022-04-04
dc.identifier.citationWillem van den Boom, Alexandros Beskos, Maria De Iorio (2022-04-04). The G-Wishart Weighted Proposal Algorithm: Efficient Posterior Computation for Gaussian Graphical Models. Journal of Computational and Graphical Statistics 31 (4) : 1215-1224. ScholarBank@NUS Repository.
dc.identifier.issn1061-8600
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/235556
dc.publisherTaylor & Francis
dc.sourceTaylor & Francis
dc.typeArticle
dc.contributor.departmentYALE-NUS COLLEGE
dc.contributor.departmentSTATISTICS & APPLIED PROBABILITY
dc.contributor.departmentDEAN'S OFFICE (YALE-NUS COLLEGE)
dc.description.sourcetitleJournal of Computational and Graphical Statistics
dc.description.volume31
dc.description.issue4
dc.description.page1215-1224
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