Large sample results for varying kernel regression estimates

DOI10.1080/10485252.2013.810742zbMath1416.62199OpenAlexW2049909519MaRDI QIDQ2863053

Hira L. Koul, Wei-xing Song

Publication date: 21 November 2013

Published in: Journal of Nonparametric Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/10485252.2013.810742

zbMATH Keywords

central limit theoremalmost sure convergenceinverse gamma distributionvarying kernel regression

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20)

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Cites Work

• Unnamed Item
• Beta kernel estimators for density functions
• Miscellanea Kernel-Type Density Estimation on the Unit Interval
• Varying kernel density estimation on \(\mathbb R_+\)
• Admissible kernel estimators of a multivariate density
• Variable bandwidth and local linear regression smoothers
• Local linear smoothers using asymmetric kernels
• Optimal asymmetric kernels
• Local linear regression smoothers and their minimax efficiencies
• Boundary modification for kernel regression
• Incorporating support constraints into nonparametric estimators of densities
• Consistency of the beta kernel density function estimator
• Density estimation using inverse and reciprocal inverse Gaussian kernels
• Hazard Rate Estimation under Random Censoring with Varying Kernels and Bandwidths
• Probability density function estimation using gamma kernels

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