Partly linear models on Riemannian manifolds
In partly linear models, the dependence of the response y on (xT, t) is modeled through the relationship y = xTβ + g(t) + ε, where ε is independent of (xT, t). We are interested in developing an estimation procedure that allows us to combine the flexibility of the partly linear models, studied by se...
| Autores: | , , |
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| Tipo de documento: | artigo |
| Estado: | Versão publicada |
| Data de publicação: | 2012 |
| País: | Argentina |
| Recursos: | Consejo Nacional de Investigaciones Científicas y Técnicas |
| Repositório: | CONICET Digital (CONICET) |
| Idioma: | inglês |
| OAI Identifier: | oai:ri.conicet.gov.ar:11336/19993 |
| Acesso em linha: | http://hdl.handle.net/11336/19993 |
| Access Level: | Acceso aberto |
| Palavra-chave: | Hypothesis Test Nonparametric Estimation Partly Linear Models Riemannian Manifolds https://purl.org/becyt/ford/1.1 https://purl.org/becyt/ford/1 |
| Resumo: | In partly linear models, the dependence of the response y on (xT, t) is modeled through the relationship y = xTβ + g(t) + ε, where ε is independent of (xT, t). We are interested in developing an estimation procedure that allows us to combine the flexibility of the partly linear models, studied by several authors, but including some variables that belong to a non-Euclidean space. The motivating application of this paper deals with the explanation of the atmospheric SO2 pollution incidents using these models when some of the predictive variables belong in a cylinder. In this paper, the estimators of β and g are constructed when the explanatory variablest take values on a Riemannian manifold and the asymptotic properties of the proposed estimators are obtained under suitable conditions. We illustrate the use of this estimation approach using an environmental data set and we explore the performance of the estimators through a simulation study. |
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