A semiparametric autorregresive spatial prediction model
Fuente:
arXiv
Gespeichert in:
| Hauptverfasser: | , , |
|---|---|
| Format: | Preprint |
| Veröffentlicht: |
2026
|
| Schlagworte: | |
| Online-Zugang: | |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| _version_ | 1866908999580909568 |
|---|---|
| author | Arancibia, Rodrigo García Llop, Pamela Lovatto, Mariel |
| author_facet | Arancibia, Rodrigo García Llop, Pamela Lovatto, Mariel |
| contents | In this paper we propose a semiparametric spatial autoregressive model that combines a linear covariate component with a nonparametrically estimated spatial term, allowing flexible dependence modeling without restrictive covariance structure while preserving interpretability. We establish asymptotic properties, including consistency and asymptotic normality, and evaluate performance through simulations and real data. Results show competitive predictive accuracy relative to geostatistical methods and improved interpretability compared to spatial econometric models. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_26041 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | A semiparametric autorregresive spatial prediction model Arancibia, Rodrigo García Llop, Pamela Lovatto, Mariel Methodology Statistics Theory In this paper we propose a semiparametric spatial autoregressive model that combines a linear covariate component with a nonparametrically estimated spatial term, allowing flexible dependence modeling without restrictive covariance structure while preserving interpretability. We establish asymptotic properties, including consistency and asymptotic normality, and evaluate performance through simulations and real data. Results show competitive predictive accuracy relative to geostatistical methods and improved interpretability compared to spatial econometric models. |
| title | A semiparametric autorregresive spatial prediction model |
| topic | Methodology Statistics Theory |
| url | https://arxiv.org/abs/2604.26041 |