User: Guest  Login
Title:

Vine copula mixture models and clustering for non-Gaussian data

Document type:
Zeitschriftenaufsatz
Author(s):
Sahin, Özge; Czado, Claudia
Abstract:
The majority of finite mixture models suffer from not allowing asymmetric tail dependencies within components and not capturing non-elliptical clusters in clustering applications. Since vine copulas are very flexible in capturing these dependencies, a novel vine copula mixture model for continuous data is proposed. The model selection and parameter estimation problems are discussed, and further, a new model-based clustering algorithm is formulated. The use of vine copulas in clustering allows fo...     »
Keywords:
Dependence, ECM algorithm, model-based clustering, multivariate finite mixtures, pair-copula, statistical learning
Dewey Decimal Classification:
510 Mathematik
Journal title:
Econometrics and Statistics
Year:
2022
Journal volume:
22
Year / month:
2022-04
Quarter:
2. Quartal
Month:
Apr
Pages contribution:
136-158
Language:
en
Fulltext / DOI:
doi:10.1016/j.ecosta.2021.08.011
Publisher:
Elsevier BV
E-ISSN:
2452-3062
Date of publication:
01.04.2022
TUM Institution:
Professur für Angewandte Mathematische Statistik
Format:
Text
 BibTeX