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Title:

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

Document type:
Zeitschriftenaufsatz
Author(s):
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...     »
Keywords:
Dependence modeling Multivariate event time data Maximum likelihood estimation Right-censoring Survival analysis Vine copulas
Dewey Decimal Classification:
510 Mathematik
Journal title:
Computational Statistics & Data Analysis
Year:
2018
Journal volume:
117
Year / month:
2018-01
Quarter:
1. Quartal
Month:
Jan
Pages contribution:
109-127
Language:
en
Fulltext / DOI:
doi:10.1016/j.csda.2017.07.010
Publisher:
Elsevier BV
E-ISSN:
0167-9473
Date of publication:
01.01.2018
TUM Institution:
Professur für Angewandte Mathematische Statistik
Format:
Text
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