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Titel:

Modelling Longitudinal Data using a Pair-Copula Decomposition of Serial Dependence

Dokumenttyp:
Zeitschriftenaufsatz
Autor(en):
Smith, M.; Min, A.; Almeida,C.; Czado,C.
Nicht-TUM Koautoren:
ja
Kooperation:
-
Abstract:
Copulas have proven to be very successful tools for the flexible modelling of cross-sectional dependence. In this paper we express the dependence structure of continuous time series data using a sequence of bivariate copulas. This corresponds to a type of decomposition recently called a ‘vine’ in the graphical models literature, where each copula is entitled a ‘pair-copula’. We propose a Bayesian approach for the estimation of this dependence structure for longitudinal data. Bayesian selection i...     »
Intellectual Contribution:
Discipline-based Research
Zeitschriftentitel:
Journal of the American Statistical Association
Jahr:
2010
Band / Volume:
105
Heft / Issue:
492
Seitenangaben Beitrag:
1467-1479
Reviewed:
ja
Sprache:
en
Status:
Erstveröffentlichung
Semester:
SS 02
Format:
Text
Urteilsbesprechung:
0
Key publication:
Ja
Peer reviewed:
Ja
International:
Ja
Book review:
Nein
commissioned:
not commissioned
Professional Journal:
Nein
Technology:
Nein
Leitbild:
;
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