Show simple item record

dc.contributor.authorTolosana Delgado, Raimon
dc.date.accessioned2012-07-18T11:42:33Z
dc.date.available2012-07-18T11:42:33Z
dc.date.created2011
dc.date.issued2011
dc.identifier.citationTolosana-Delgado, R. Unmixing compositional data with Bayesian techniques. A: International Workshop on Compositional Data Analysis. "Proceedings of the 4th International Workshop on Compositional Data Analysis (2011)". Sant Feliu de Guíxols: Centre Internacional de Mètodes Numèrics en Enginyeria (CIMNE), 2011, p. 1-5.
dc.identifier.isbn978-84-87867-76-7
dc.identifier.urihttp://hdl.handle.net/2117/16292
dc.description.abstractA general problem in compositional data analysis is the unmixing of a composition into a series of pure endmembers. In its most complex version, one does neither know the composition of these endmembers, nor their relative contribution to each observed composition. The problem is particularly cumbersome if the number of endmembers is larger than the number of observed components. This contribution proposes a possible solution of this under-determined problem. The proposed method starts assuming that the endmember composition is known. Then, a geometric characterization of the problem allows to nd the set of possible endmember proportions compatible with the observed composition. Within this set any solution may be valid, but some are more likely than other. To use this idea and choose the "most likely" solution in each case, the problem can be tackled with Bayesian Markov-Chain Monte-Carlo techniques. Finally, once we are familiar with MCMC, it is quite traightforward to allow the endmember compositions to randomly vary, and use the same MCMC to estimate the endmember composition most compatible with the studied data.
dc.format.extent5 p.
dc.language.isoeng
dc.publisherCentre Internacional de Mètodes Numèrics en Enginyeria (CIMNE)
dc.subjectÀrees temàtiques de la UPC::Matemàtiques i estadística::Matemàtica aplicada a les ciències
dc.subject.lcshBayesian statistical decision theory
dc.titleUnmixing compositional data with Bayesian techniques
dc.typeConference report
dc.subject.lemacEstadística bayesiana
dc.contributor.groupUniversitat Politècnica de Catalunya. LIM/UPC - Laboratori d'Enginyeria Marítima
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttp://congress.cimne.com/codawork11/Admin/Files/FilePaper/p56.pdf
dc.rights.accessOpen Access
drac.iddocument9482003
dc.description.versionPostprint (published version)
upcommons.citation.authorTolosana-Delgado, R.
upcommons.citation.contributorInternational Workshop on Compositional Data Analysis
upcommons.citation.pubplaceSant Feliu de Guíxols
upcommons.citation.publishedtrue
upcommons.citation.publicationNameProceedings of the 4th International Workshop on Compositional Data Analysis (2011)
upcommons.citation.startingPage1
upcommons.citation.endingPage5


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record

All rights reserved. This work is protected by the corresponding intellectual and industrial property rights. Without prejudice to any existing legal exemptions, reproduction, distribution, public communication or transformation of this work are prohibited without permission of the copyright holder