Copula-based models for correlated circular data
Fuente:
arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866910475113988096 |
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| author | Lagona, Francesco Mingione, Marco |
| author_facet | Lagona, Francesco Mingione, Marco |
| contents | We exploit Gaussian copulas to specify a class of multivariate circular distributions and obtain parametric models for the analysis of correlated circular data. This approach provides a straightforward extension of traditional multivariate normal models to the circular setting, without imposing restrictions on the marginal data distribution nor requiring overwhelming routines for parameter estimation. The proposal is illustrated on two case studies of animal orientation and sea currents, where we propose an autoregressive model for circular time series and a geostatistical model for circular spatial series. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_04085 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Copula-based models for correlated circular data Lagona, Francesco Mingione, Marco Methodology Statistics Theory We exploit Gaussian copulas to specify a class of multivariate circular distributions and obtain parametric models for the analysis of correlated circular data. This approach provides a straightforward extension of traditional multivariate normal models to the circular setting, without imposing restrictions on the marginal data distribution nor requiring overwhelming routines for parameter estimation. The proposal is illustrated on two case studies of animal orientation and sea currents, where we propose an autoregressive model for circular time series and a geostatistical model for circular spatial series. |
| title | Copula-based models for correlated circular data |
| topic | Methodology Statistics Theory |
| url | https://arxiv.org/abs/2406.04085 |