Semi-functional partial linear regression with measurement error: An approach based on $k$NN estimation
Fuente:
arXiv
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| Autores principales: | , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Acceso en línea: | |
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| _version_ | 1866916486606487552 |
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| author | Novo, Silvia Aneiros, Germán Vieu, Philippe |
| author_facet | Novo, Silvia Aneiros, Germán Vieu, Philippe |
| contents | This paper focuses on a semiparametric regression model in which the response variable is explained by the sum of two components. One of them is parametric (linear), the corresponding explanatory variable is measured with additive error and its dimension is finite ($p$). The other component models, in a nonparametric way, the effect of a functional variable (infinite dimension) on the response. $k$-NN based estimators are proposed for each component, and some asymptotic results are obtained. A simulation study illustrates the behaviour of such estimators for finite sample sizes, while an application to real data shows the usefulness of our proposal. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2402_11292 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Semi-functional partial linear regression with measurement error: An approach based on $k$NN estimation Novo, Silvia Aneiros, Germán Vieu, Philippe Methodology 62G05, 62G08, 62G20 This paper focuses on a semiparametric regression model in which the response variable is explained by the sum of two components. One of them is parametric (linear), the corresponding explanatory variable is measured with additive error and its dimension is finite ($p$). The other component models, in a nonparametric way, the effect of a functional variable (infinite dimension) on the response. $k$-NN based estimators are proposed for each component, and some asymptotic results are obtained. A simulation study illustrates the behaviour of such estimators for finite sample sizes, while an application to real data shows the usefulness of our proposal. |
| title | Semi-functional partial linear regression with measurement error: An approach based on $k$NN estimation |
| topic | Methodology 62G05, 62G08, 62G20 |
| url | https://arxiv.org/abs/2402.11292 |