THE UNIQUENESS OF CROSS-VALIDATION SELECTED SMOOTHING PARAMETERS IN KERNEL ESTIMATION OF NONPARAMETRIC MODELS

DOI10.1017/S0266466605050504zbMath1081.62027MaRDI QIDQ3375349

Q. Li, Jian Xin Zhou

Publication date: 8 March 2006

Published in: Econometric Theory (Search for Journal in Brave)

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Estimation in multivariate analysis (62H12) Asymptotic properties of nonparametric inference (62G20)

Related Items (7)

A Bayesian approach to bandwidth selection for multivariate kernel regression with an application to state-price density estimation ⋮ A multivariate non-parametric kernel estimator for global sensitivity analysis ⋮ Bayesian bandwidth estimation for local linear fitting in nonparametric regression models ⋮ SMOOTH VARYING-COEFFICIENT ESTIMATION AND INFERENCE FOR QUALITATIVE AND QUANTITATIVE DATA ⋮ Nonparametric regression with weakly dependent data: the discrete and continuous regressor case ⋮ Nonparametric estimation of conditional quantile functions in the presence of irrelevant covariates ⋮ Multivariate Local Polynomial Kernel Estimators: Leading Bias and Asymptotic Distribution

Cites Work

• Optimal bandwidth selection in nonparametric regression function estimation
• Nonparametric estimation of distributions with categorical and continuous data
• How Far Are Automatically Chosen Regression Smoothing Parameters From Their Optimum?

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