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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2023
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2401.01894 |
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| _version_ | 1866917558196633600 |
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| author | La Fuente, Luis González-De Nieto-Reyes, Alicia Terán, Pedro |
| author_facet | La Fuente, Luis González-De Nieto-Reyes, Alicia Terán, Pedro |
| contents | Statistical depth functions are a standard tool in nonparametric statistics to extend order-based univariate methods to the multivariate setting. Since there is no universally accepted total order for fuzzy data (even in the univariate case) and there is a lack of parametric models, a fuzzy extension of depth-based methods is very interesting. In this paper, we adapt projection depth and $L^{r}$-type depth to the fuzzy setting, studying their properties and illustrating their behaviour with a real data example. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_01894 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Projection depth and $L^r$-type depths for fuzzy random variables La Fuente, Luis González-De Nieto-Reyes, Alicia Terán, Pedro Statistics Theory Statistical depth functions are a standard tool in nonparametric statistics to extend order-based univariate methods to the multivariate setting. Since there is no universally accepted total order for fuzzy data (even in the univariate case) and there is a lack of parametric models, a fuzzy extension of depth-based methods is very interesting. In this paper, we adapt projection depth and $L^{r}$-type depth to the fuzzy setting, studying their properties and illustrating their behaviour with a real data example. |
| title | Projection depth and $L^r$-type depths for fuzzy random variables |
| topic | Statistics Theory |
| url | https://arxiv.org/abs/2401.01894 |