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Titel:

Vine copula based likelihood estimation of dependence patterns in multivariate event time data

Dokumenttyp:
Zeitschriftenaufsatz
Autor(en):
Barthel, Nicole; Geerdens, Candida; Killiches, Matthias; Janssen, Paul; Czado, Claudia
Abstract:
In many studies multivariate event time data are generated from clusters having a possibly complex association pattern. Flexible models are needed to capture this dependence. Vine copulas serve this purpose. Inference methods for vine copulas are available for complete data. Event time data, however, are often subject to right-censoring. As a consequence, the existing inferential tools, e.g. likelihood estimation, need to be adapted. A two-stage estimation approach is proposed. First, the margin...     »
Stichworte:
Dependence modeling Multivariate event time data Maximum likelihood estimation Right-censoring Survival analysis Vine copulas
Dewey Dezimalklassifikation:
510 Mathematik
Zeitschriftentitel:
Computational Statistics & Data Analysis
Jahr:
2018
Band / Volume:
117
Jahr / Monat:
2018-01
Quartal:
1. Quartal
Monat:
Jan
Seitenangaben Beitrag:
109-127
Sprache:
en
Volltext / DOI:
doi:10.1016/j.csda.2017.07.010
Verlag / Institution:
Elsevier BV
E-ISSN:
0167-9473
Publikationsdatum:
01.01.2018
TUM Einrichtung:
Professur für Angewandte Mathematische Statistik
Format:
Text
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