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AuthorWinzenborg, Insadc.contributor.author
Date of accession2016-03-15T06:23:11Zdc.date.accessioned
Available in OPARU since2016-03-15T06:23:11Zdc.date.available
Year of creation2011dc.date.created
AbstractIn this thesis the nonparametric functional principal component analysis is extended to spatial data. The estimation is implemented in an R package and the implementation is evaluated comparing estimated eigenfunctions of realizations of a Wiener process to the theoretic ones. Furthermore, consistency results for the estimators are derived theoretically. Both, the one- and the two-dimensional method are used to evaluate several real data examples from the medical field, especially diagnostics.dc.description.abstract
Languageendc.language.iso
PublisherUniversität Ulmdc.publisher
LicenseStandard (Fassung vom 01.10.2008)dc.rights
Link to license texthttps://oparu.uni-ulm.de/xmlui/license_v2dc.rights.uri
KeywordFunctional data analysisdc.subject
KeywordSpatial statisticsdc.subject
Dewey Decimal GroupDDC 510 / Mathematicsdc.subject.ddc
LCSHPrincipal components analysisdc.subject.lcsh
TitleSpatial functional principal component analysis and its application in diagnosticsdc.title
Resource typeDissertationdc.type
DOIhttp://dx.doi.org/10.18725/OPARU-1802dc.identifier.doi
PPN663906075dc.identifier.ppn
URNhttp://nbn-resolving.de/urn:nbn:de:bsz:289-vts-76855dc.identifier.urn
GNDKomponentenanalysedc.subject.gnd
GNDPsychologische Diagnostikdc.subject.gnd
FacultyFakultät für Mathematik und Wirtschaftswissenschaftenuulm.affiliationGeneral
Date of activation2011-06-30T08:47:58Zuulm.freischaltungVTS
Peer reviewneinuulm.peerReview
Shelfmark print versionZ: J-H 14.184; N: J-H 9.895uulm.shelfmark
DCMI TypeTextuulm.typeDCMI
VTS ID7685uulm.vtsID
CategoryPublikationenuulm.category
Bibliographyuulmuulm.bibliographie


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