Tail dependence of a pareto process

doi:10.1007/978-3-319-05323-3_17

Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/34775

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Campo DC	Valor	Idioma
dc.contributor.author	Ferreira, Marta Susana	por
dc.date.accessioned	2015-04-10T11:40:35Z	-
dc.date.available	2015-04-10T11:40:35Z	-
dc.date.issued	2014-04	-
dc.identifier.isbn	978-3-319-05323-3	-
dc.identifier.isbn	978-3-319-05322-6	-
dc.identifier.issn	2194-7767	por
dc.identifier.uri	https://hdl.handle.net/1822/34775	-
dc.description.abstract	Heavy-tailed autoregressive processes defined with minimum or maximum operator are good alternatives to classic linear ARMA with heavy tail noises, in what concerns extreme values modeling. In this paper we present a full characterization of the tail dependence of the autoregressive minima process, Yeh-Arnold-Robertson Pareto(III).	por
dc.description.sponsorship	This research was financed by FEDER Funds through "Programa Operacional Factores de Competitividade - COMPETE"	por
dc.description.sponsorship	Portuguese Funds through FCT - "Fundação para a Ciência e a Tecnologia", within the Project PEst-OE/MAT/UI0013/2014	por
dc.language.iso	eng	por
dc.publisher	Springer	por
dc.rights	restrictedAccess	por
dc.title	Tail dependence of a pareto process	por
dc.type	bookPart	por
dc.peerreviewed	yes	por
dc.relation.publisherversion	http://link.springer.com/chapter/10.1007/978-3-319-05323-3_17	-
sdum.publicationstatus	published	por
oaire.citationStartPage	177	por
oaire.citationEndPage	185	por
oaire.citationTitle	New Advances in Statistical Modeling and Applications	por
dc.identifier.doi	10.1007/978-3-319-05323-3_17	por
sdum.journal	Studies in Theoretical and Applied Statistics. Selected Papers of the Statistical Societies	por
sdum.bookTitle	New Advances in Statistical Modeling and Applications	por
Aparece nas coleções:	CMAT - Artigos em atas de conferências e capítulos de livros com arbitragem / Papers in proceedings of conferences and book chapters with peer review