Kernel estimation of discontinuous regression functions

DOI10.1016/S0167-7152(99)00165-0zbMath0968.62042OpenAlexW2089048038MaRDI QIDQ1976510

Kee-Hoon Kang, Cheol-Woo Park, Ja-Yong Koo

Publication date: 17 September 2001

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0167-7152(99)00165-0

zbMATH Keywords

rate of convergenceweak convergencechange-pointsjump sizeboundary kerneljump locationL2 convergence

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Density estimation (62G07)

Related Items (8)

Bayesian curve fitting for discontinuous functions using an overcomplete system with multiple kernels ⋮ Wavelet estimation of a regression function with a sharp change point in a random design ⋮ Local linear kernel estimation of the discontinuous regression function ⋮ Fitting jump additive models ⋮ A jump-detecting procedure based on spline estimation ⋮ Jump-preserving regression and smoothing using local linear fitting: a compromise ⋮ Estimation of a regression function with a sharp change point using boundary wavelets ⋮ A variational inference for the Lévy adaptive regression with multiple kernels

Uses Software

• wavethresh

Cites Work

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• A lower bound on the error in nonparametric regression type problems
• Nonparametric regression analysis of longitudinal data
• Change-points in nonparametric regression analysis
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• Minimax estimation of sharp change points
• Optimal global rates of convergence for nonparametric regression
• Smoothing with Split Linear Fits
• Asymptotically optimal difference-based estimation of variance in nonparametric regression
• Detecting Change Points by Fourier Analysis
• Detection of the number, locations and magnitudes of jumps
• Jump and sharp cusp detection by wavelets
• Statistical methods for DNA sequence segmentation

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