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dc.contributor.authorOrtells Sesé, Robert
dc.contributor.authorEgozcue Rubí, Juan José
dc.contributor.authorOrtego Martínez, María Isabel
dc.contributor.authorGarola Crespo, Àlvar
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria Civil i Ambiental
dc.date.accessioned2017-03-03T15:22:14Z
dc.date.issued2016
dc.identifier.citationOrtells, R., Egozcue, J. J., Ortego, M.I., Garola, A. Relationship between the popularity of key words in the Google browser and the evolution of worldwide financial indices. A: "Compositional data analysis". Berlín: Springer, 2016, p. 145-165.
dc.identifier.isbn978-3-319-44811-4
dc.identifier.urihttp://hdl.handle.net/2117/101920
dc.description.abstractThe authoritative contributions gathered in this volume reflect the state of the art in compositional data analysis (CoDa). The respective chapters cover all aspects of CoDa, ranging from mathematical theory, statistical methods and techniques to its broad range of applications in geochemistry, the life sciences and other disciplines. The selected and peer-reviewed papers were originally presented at the 6th International Workshop on Compositional Data Analysis, CoDaWork 2015, held in L’Escala (Girona), Spain. Compositional data is defined as vectors of positive components and constant sum, and, more generally, all those vectors representing parts of a whole which only carry relative information. Examples of compositional data can be found in many different fields such as geology, chemistry, economics, medicine, ecology and sociology. As most of the classical statistical techniques are incoherent on compositions, in the 1980s John Aitchison proposed the log-ratio approach to CoDa. This became the foundation of modern CoDa, which is now based on a specific geometric structure for the simplex, an appropriate representation of the sample space of compositional data. The International Workshops on Compositional Data Analysis offer a vital discussion forum for researchers and practitioners concerned with the statistical treatment and modelling of compositional data or other constrained data sets and the interpretation of models and their applications. The goal of the workshops is to summarize and share recent developments, and to identify important lines of future research.
dc.format.extent21 p.
dc.language.isoeng
dc.publisherSpringer
dc.subjectÀrees temàtiques de la UPC::Matemàtiques i estadística::Investigació operativa::Optimització
dc.subject.lcshProgramming (Mathematics)
dc.subject.otherFinancial markets
dc.subject.otherGoogle searches
dc.subject.otherStock market indices
dc.subject.otherCompositional data
dc.subject.otherMultiple linear regression
dc.titleRelationship between the popularity of key words in the Google browser and the evolution of worldwide financial indices
dc.typePart of book or chapter of book
dc.subject.lemacInvestigació operativa
dc.contributor.groupUniversitat Politècnica de Catalunya. COSDA-UPC - COmpositional and Spatial Data Analysis
dc.identifier.doi10.1007/978-3-319-44811-4_10
dc.relation.publisherversionhttp://www.springer.com/fr/book/9783319448107?wt_mc=ThirdParty.SpringerLink.3.EPR653.About_eBook
dc.rights.accessRestricted access - publisher's policy
local.identifier.drac19674442
dc.description.versionPreprint
dc.date.lift10000-01-01
local.citation.authorOrtells, R.; Egozcue, J. J.; Ortego, M.I.; Garola, A.
local.citation.pubplaceBerlín
local.citation.publicationNameCompositional data analysis
local.citation.startingPage145
local.citation.endingPage165


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