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dc.contributor.authorDalla Valle, L
dc.contributor.editorBalakrishnan N
dc.contributor.editorBrandimarte P
dc.contributor.editorEveritt B
dc.contributor.editorMolenberghs G
dc.contributor.editorPiegorsch W
dc.contributor.editorRuggeri F
dc.date.accessioned2017-05-22T09:33:26Z
dc.date.available2017-05-22T09:33:26Z
dc.date.issued2017-12-20
dc.identifier.urihttp://hdl.handle.net/10026.1/9294
dc.description.abstract

This article introduces some of the most popular techniques of data integration that allow the combination of information coming from various sources. The illustration focuses, in particular, on the Bayesian generalized Heckman methodology and the data calibration methodology based on vines and nonparametric Bayesian networks.

dc.format.extent1-6
dc.language.isoen
dc.publisherJohn Wiley & Sons
dc.relation.ispartofWiley StatsRef: Statistics Reference Online
dc.subject49 Mathematical Sciences
dc.subject4905 Statistics
dc.titleData Integration
dc.typechapter
plymouth.publisher-urlhttp://dx.doi.org/10.1002/9781118445112.stat08014
plymouth.publication-statusPublished online
dc.identifier.doi10.1002/9781118445112.stat08014
plymouth.organisational-group/Plymouth
plymouth.organisational-group/Plymouth/Faculty of Science and Engineering
plymouth.organisational-group/Plymouth/Faculty of Science and Engineering/School of Engineering, Computing and Mathematics
plymouth.organisational-group/Plymouth/REF 2021 Researchers by UoA
plymouth.organisational-group/Plymouth/REF 2021 Researchers by UoA/EXTENDED UoA 10 - Mathematical Sciences
plymouth.organisational-group/Plymouth/REF 2021 Researchers by UoA/UoA10 Mathematical Sciences
plymouth.organisational-group/Plymouth/Users by role
plymouth.organisational-group/Plymouth/Users by role/Academics
dc.rights.embargoperiodNot known
rioxxterms.versionofrecord10.1002/9781118445112.stat08014
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserved
rioxxterms.typeBook chapter


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