Convergence rates for average square errors for kernel smoothing estimators
Author:
Publisher
Informa UK Limited
Subject
Statistics, Probability and Uncertainty,Statistics and Probability
Link
http://www.tandfonline.com/doi/pdf/10.1080/10485250108832850
Reference15 articles.
1. Local Linear Regression Smoothers and Their Minimax Efficiencies
2. Loss and risk in smoothing parameter selection
3. Central limit theorem for integrated square error of multivariate nonparametric density estimators
4. Integrated Square Error Properties of Kernel Estimators of Regression Functions
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1. Uniformly Consistency of the Cauchy-Transformation Kernel Density Estimation Underlying Strong Mixing;Applied Mathematics & Information Sciences;2013-02-01
2. Central limit theorem for quadratic errors of Nadaraya–Watson regression estimator under dependence;Journal of the Korean Statistical Society;2011-12
3. The central limit theorem for degenerate variableU-statistics under dependence;Journal of Nonparametric Statistics;2011-09
4. Nonparametric least squares estimation in derivative families;Journal of Econometrics;2010-08
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