Vine copulas as a way to describe and analyze multi-variate dependence in econometrics: Computational motivation and comparison with Bayesian networks and fuzzy approaches
In the last decade, vine copulas emerged as a new efficient techniques for describing and analyzing multi-variate dependence in econometrics; see, e.g., [1, 2, 3, 7, 9, 10, 11, 13, 14, 21]. Our experience has shown, however, that while these techniques have been successfully applied to many practica...
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th-cmuir.6653943832-456332018-01-24T06:14:15Z Vine copulas as a way to describe and analyze multi-variate dependence in econometrics: Computational motivation and comparison with Bayesian networks and fuzzy approaches Songsak Sriboonchitta Jianxu Liu Vladik Kreinovich Hung T. Nguyen In the last decade, vine copulas emerged as a new efficient techniques for describing and analyzing multi-variate dependence in econometrics; see, e.g., [1, 2, 3, 7, 9, 10, 11, 13, 14, 21]. Our experience has shown, however, that while these techniques have been successfully applied to many practical problems of econometrics, there is still a lot of confusion and misunderstanding related to vine copulas. In this paper, we provide a motivation for this new technique from the computational viewpoint. We show that other techniques used to described dependence - Bayesian networks and fuzzy techniques - can be viewed as a particular case of vine copulas. © Springer International Publishing Switzerland 2014. 2018-01-24T06:14:15Z 2018-01-24T06:14:15Z 2014-01-01 Book Series 21945357 2-s2.0-84897859595 10.1007/978-3-319-03395-2_11 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84897859595&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/45633 |
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In the last decade, vine copulas emerged as a new efficient techniques for describing and analyzing multi-variate dependence in econometrics; see, e.g., [1, 2, 3, 7, 9, 10, 11, 13, 14, 21]. Our experience has shown, however, that while these techniques have been successfully applied to many practical problems of econometrics, there is still a lot of confusion and misunderstanding related to vine copulas. In this paper, we provide a motivation for this new technique from the computational viewpoint. We show that other techniques used to described dependence - Bayesian networks and fuzzy techniques - can be viewed as a particular case of vine copulas. © Springer International Publishing Switzerland 2014. |
| format |
Book Series |
| author |
Songsak Sriboonchitta Jianxu Liu Vladik Kreinovich Hung T. Nguyen |
| spellingShingle |
Songsak Sriboonchitta Jianxu Liu Vladik Kreinovich Hung T. Nguyen Vine copulas as a way to describe and analyze multi-variate dependence in econometrics: Computational motivation and comparison with Bayesian networks and fuzzy approaches |
| author_facet |
Songsak Sriboonchitta Jianxu Liu Vladik Kreinovich Hung T. Nguyen |
| author_sort |
Songsak Sriboonchitta |
| title |
Vine copulas as a way to describe and analyze multi-variate dependence in econometrics: Computational motivation and comparison with Bayesian networks and fuzzy approaches |
| title_short |
Vine copulas as a way to describe and analyze multi-variate dependence in econometrics: Computational motivation and comparison with Bayesian networks and fuzzy approaches |
| title_full |
Vine copulas as a way to describe and analyze multi-variate dependence in econometrics: Computational motivation and comparison with Bayesian networks and fuzzy approaches |
| title_fullStr |
Vine copulas as a way to describe and analyze multi-variate dependence in econometrics: Computational motivation and comparison with Bayesian networks and fuzzy approaches |
| title_full_unstemmed |
Vine copulas as a way to describe and analyze multi-variate dependence in econometrics: Computational motivation and comparison with Bayesian networks and fuzzy approaches |
| title_sort |
vine copulas as a way to describe and analyze multi-variate dependence in econometrics: computational motivation and comparison with bayesian networks and fuzzy approaches |
| publishDate |
2018 |
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https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84897859595&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/45633 |
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