Kernel regression estimation when the regressor takes values in metric space

DOI10.1016/S1631-073X(02)00012-2zbMath1020.62034OpenAlexW2077303640MaRDI QIDQ1871541

Sophie Dabo-Niang, Noureddine Rhomari

Publication date: 8 May 2003

Published in: Comptes Rendus. Mathématique. Académie des Sciences, Paris (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s1631-073x(02)00012-2

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Asymptotic properties of nonparametric inference (62G20)

Related Items (11)

Nonparametric Quantile Regression Estimation for Functional Dependent Data ⋮ Nonparametric estimation of the conditional mode when the regressor is functional ⋮ Non parametric estimations of the conditional density and mode when the regressor and the response are curves ⋮ Kernel regression estimation for continuous spatial processes ⋮ Kernel density estimator in an infinite-dimensional space with a rate of convergence in the case of diffusion process. ⋮ Nearest neighbor classification in infinite dimension ⋮ Kernel regression estimation in a Banach space ⋮ Note on conditional mode estimation for functional dependent data ⋮ Rate of uniform consistency for nonparametric estimates with functional variables ⋮ Functional semiparametric partially linear model with autoregressive errors ⋮ Kernel regression estimation when the regressor takes values in metric space

Uses Software

• fda (R)

Cites Work

• Kernel regression estimation in a Banach space
• On the almost everywhere convergence of nonparametric regression function estimates
• Functional data analysis
• Linear processes in function spaces. Theory and applications
• Density estimation in an infinite dimensional space: Application to diffusion processes
• Kernel regression estimation when the regressor takes values in metric space
• Functional nonparametric model for time series: a fractal approach for dimension reduction
• Differentiation Theorem for Gaussian Measures on Hilbert Space
• A relation between Chung's and Strassen's laws of the iterated logarithm
• The rates of convergence of kernel regression estimates and classification rules
• Rates of convergence of nearest neighbor estimation under arbitrary sampling
• Dimension fractale et estimation de la régression dans des espaces vectoriels semi-normés

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