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dc.identifier.urihttp://hdl.handle.net/11401/78493
dc.description.sponsorshipThis work is sponsored by the Stony Brook University Graduate School in compliance with the requirements for completion of degree.en_US
dc.formatMonograph
dc.format.mediumElectronic Resourceen_US
dc.typeDissertation
dcterms.available2018-11-12T17:50:31Z
dcterms.contributorDouady, Raphaelen_US
dcterms.creatorYe, Xingxing
dcterms.dateAccepted2018-11-12T17:50:31Z
dcterms.dateSubmitted2018-11-12T17:50:31Z
dcterms.descriptionDepartment of Applied Mathematics and Statistics.en_US
dcterms.extent60 pg.en_US
dcterms.formatMonograph
dcterms.identifierhttp://hdl.handle.net/11401/78493
dcterms.issued2018-01-05
dcterms.issued2018
dcterms.provenanceMade available in DSpace on 2018-11-12T17:50:31Z (GMT). No. of bitstreams: 1 Ye_grad.sunysb_0771E_13631.pdf: 3372647 bytes, checksum: 01691efe949db2eb3af06e4ee813bec7 (MD5) Previous issue date: 2018-01-05en
dcterms.subjectApplied mathematics
dcterms.subjectindicator
dcterms.subjectnetwork
dcterms.subjectnonlinear
dcterms.subjectPolyModel
dcterms.subjectsystemic risk
dcterms.subjectvalidation
dcterms.titleSystemic Risk Indicators Based on Nonlinear Model
dcterms.typeDissertation


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