Rates of strong uniform consistency for local least squares kernel regression estimators
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Publication:2467389
DOI10.1016/j.spl.2007.03.037zbMath1128.62046OpenAlexW2085668762MaRDI QIDQ2467389
Publication date: 21 January 2008
Published in: Statistics \& Probability Letters (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.spl.2007.03.037
rate of convergencelocal polynomial fittingkernel estimationderivative estimationstrong uniform consistencylocal linear least squares kernel estimatoruniform limit law of the logarithm
Nonparametric regression and quantile regression (62G08) Estimation in multivariate analysis (62H12) Asymptotic properties of nonparametric inference (62G20) Strong limit theorems (60F15)
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Uses Software
Cites Work
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- Sharper bounds for Gaussian and empirical processes
- General asymptotic confidence bands based on kernel-type function estimators
- Multivariate locally weighted least squares regression
- Rates of strong uniform consistency for multivariate kernel density estimators. (Vitesse de convergence uniforme presque sûre pour des estimateurs à noyaux de densités multivariées)
- Design-adaptive Nonparametric Regression
- The Law of the Iterated Logarithm for Empirical Distribution
- An empirical process approach to the uniform consistency of kernel-type function estimators
- On consistency of kernel density estimators for randomly censored data: Rates holding uniformly over adaptive intervals
