Goodness-of-fit tests for multi-dimensional copulas: Expanding application to historical drought data
The question of how to choose a copula model that best fits a given dataset is a predominant limitation of the copula approach, and the present study aims to investigate the techniques of goodness-of-fit tests for multi-dimensional copulas. A goodness-of-fit test based on Rosenblatt's transform...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2013-01-01
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| Series: | Water Science and Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1674237015302222 |
| _version_ | 1811322662248513536 |
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| author | Ming-wei Ma Li-liang Ren Song-bai Song Jia-li Song Shan-hu Jiang |
| author_facet | Ming-wei Ma Li-liang Ren Song-bai Song Jia-li Song Shan-hu Jiang |
| author_sort | Ming-wei Ma |
| collection | DOAJ |
| description | The question of how to choose a copula model that best fits a given dataset is a predominant limitation of the copula approach, and the present study aims to investigate the techniques of goodness-of-fit tests for multi-dimensional copulas. A goodness-of-fit test based on Rosenblatt's transformation was mathematically expanded from two dimensions to three dimensions and procedures of a bootstrap version of the test were provided. Through stochastic copula simulation, an empirical application of historical drought data at the Lintong Gauge Station shows that the goodness-of-fit tests perform well, revealing that both trivariate Gaussian and Student t copulas are acceptable for modeling the dependence structures of the observed drought duration, severity, and peak. The goodness-of-fit tests for multi-dimensional copulas can provide further support and help a lot in the potential applications of a wider range of copulas to describe the associations of correlated hydrological variables. However, for the application of copulas with the number of dimensions larger than three, more complicated computational efforts as well as exploration and parameterization of corresponding copulas are required. |
| first_indexed | 2024-04-13T13:39:53Z |
| format | Article |
| id | doaj.art-4a70ce84a53743ea825bb235b4547d0d |
| institution | Directory Open Access Journal |
| issn | 1674-2370 |
| language | English |
| last_indexed | 2024-04-13T13:39:53Z |
| publishDate | 2013-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Water Science and Engineering |
| spelling | doaj.art-4a70ce84a53743ea825bb235b4547d0d2022-12-22T02:44:40ZengElsevierWater Science and Engineering1674-23702013-01-0161183010.3882/j.issn.1674-2370.2013.01.002Goodness-of-fit tests for multi-dimensional copulas: Expanding application to historical drought dataMing-wei Ma0Li-liang Ren1Song-bai Song2Jia-li Song3Shan-hu Jiang4State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, P. R. ChinaState Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, P. R. ChinaCollege of Water Resources and Architectural Engineering, Northwest A&F University, Yangling 712100, P. R. ChinaBusiness School, Hohai University, Nanjing 211100, P. R. ChinaState Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, P. R. ChinaThe question of how to choose a copula model that best fits a given dataset is a predominant limitation of the copula approach, and the present study aims to investigate the techniques of goodness-of-fit tests for multi-dimensional copulas. A goodness-of-fit test based on Rosenblatt's transformation was mathematically expanded from two dimensions to three dimensions and procedures of a bootstrap version of the test were provided. Through stochastic copula simulation, an empirical application of historical drought data at the Lintong Gauge Station shows that the goodness-of-fit tests perform well, revealing that both trivariate Gaussian and Student t copulas are acceptable for modeling the dependence structures of the observed drought duration, severity, and peak. The goodness-of-fit tests for multi-dimensional copulas can provide further support and help a lot in the potential applications of a wider range of copulas to describe the associations of correlated hydrological variables. However, for the application of copulas with the number of dimensions larger than three, more complicated computational efforts as well as exploration and parameterization of corresponding copulas are required.http://www.sciencedirect.com/science/article/pii/S1674237015302222goodness-of-fit testmulti-dimensional copulasstochastic simulationRosenblatt's transformationbootstrap approachdrought data |
| spellingShingle | Ming-wei Ma Li-liang Ren Song-bai Song Jia-li Song Shan-hu Jiang Goodness-of-fit tests for multi-dimensional copulas: Expanding application to historical drought data Water Science and Engineering goodness-of-fit test multi-dimensional copulas stochastic simulation Rosenblatt's transformation bootstrap approach drought data |
| title | Goodness-of-fit tests for multi-dimensional copulas: Expanding application to historical drought data |
| title_full | Goodness-of-fit tests for multi-dimensional copulas: Expanding application to historical drought data |
| title_fullStr | Goodness-of-fit tests for multi-dimensional copulas: Expanding application to historical drought data |
| title_full_unstemmed | Goodness-of-fit tests for multi-dimensional copulas: Expanding application to historical drought data |
| title_short | Goodness-of-fit tests for multi-dimensional copulas: Expanding application to historical drought data |
| title_sort | goodness of fit tests for multi dimensional copulas expanding application to historical drought data |
| topic | goodness-of-fit test multi-dimensional copulas stochastic simulation Rosenblatt's transformation bootstrap approach drought data |
| url | http://www.sciencedirect.com/science/article/pii/S1674237015302222 |
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