A functional spatial autoregressive model using signatures
Fuente:
arXiv
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| Format: | Preprint |
| Veröffentlicht: |
2023
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| _version_ | 1866914709876244480 |
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| author | Frévent, Camille |
| author_facet | Frévent, Camille |
| contents | We propose a new approach to the autoregressive spatial functional model, based on the notion of signature, which represents a function as an infinite series of its iterated integrals. It presents the advantage of being applicable to a wide range of processes. After having provided theoretical guarantees to the proposed model, we have shown in a simulation study and on a real data set that this new approach presents competitive performances compared to the traditional model. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2303_12378 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | A functional spatial autoregressive model using signatures Frévent, Camille Methodology We propose a new approach to the autoregressive spatial functional model, based on the notion of signature, which represents a function as an infinite series of its iterated integrals. It presents the advantage of being applicable to a wide range of processes. After having provided theoretical guarantees to the proposed model, we have shown in a simulation study and on a real data set that this new approach presents competitive performances compared to the traditional model. |
| title | A functional spatial autoregressive model using signatures |
| topic | Methodology |
| url | https://arxiv.org/abs/2303.12378 |