Título:
Asymptotic normality of the Nadaraya–Watson estimator for nonstationary functional data and applications to telecommunications
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Autor:
Bertin, Karine
Aspirot, Laura
Perera, Gonzalo
Aspirot, Laura
Perera, Gonzalo
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Tipo de documento:
Preprint
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Palabras clave:
Nonparametric regression
Functional data
Asymptotic normality
Nonstationarity
Functional data
Asymptotic normality
Nonstationarity
Descriptores:
Telecomunicaciones
Año de publicación:
2007
Contenido:
Resumen:
We study a nonparametric regression model, where the explanatory variable is nonstationary dependent functional data and the response variable is scalar. Assuming that the explanatory variable is a nonstationary mixture of stationary processes and general conditions of dependence of the observations (implied in particular by weak dependence), we obtain the asymptotic normality of the Nadaraya–Watson estimator. Under some additional regularity assumptions on the regression function, we obtain asymptotic confidence intervals for the regression function. We apply this result to estimate the quality of service for an end-to-end connection on a network
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Citación:
Aspirot, L., Bertine, K., Perera, G. Asymptotic normality of the Nadaraya–Watson estimator for nonstationary functional data and applications to telecommunications [Preprint] Publicado en Journal of Nonparametric Statistics, 2009, v.21, no.5. doi: 10.1080/10485250902878655
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Departamento académico:
Telecomunicaciones
Grupo de investigación:
Análisis de Redes, Tráfico y Estadísticas de Servicios
Licencia:
Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0)
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| Ficheros | Descripción | Tamaño | Formato | ||
|---|---|---|---|---|---|
| ABP09.pdf | — | 222.01 KB | Adobe PDF |