Asymptotic bias and variance of a kernel-based estimator for the location of a discontinuity

DOI10.1080/10485259708832714zbMath0881.62053OpenAlexW1974285161MaRDI QIDQ4352133

Alun Lloyd Pope, Inge Koch

Publication date: 28 August 1997

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

Full work available at URL: https://doi.org/10.1080/10485259708832714

zbMATH Keywords

bandwidthkernel smoothingdiscontinuitiesedge locationdiscrete Canny estimation

Mathematics Subject Classification ID

Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20)

Cites Work

• Minimax theory of image reconstruction
• Estimation of a noisy discrete-time step function: Bayes and empirical Bayes approaches
• Extremes and related properties of random sequences and processes
• Estimating the number of change-points via Schwarz' criterion
• Change-points in nonparametric regression analysis
• Kernel-type estimators of jump points and values of a regression function
• A note on mse coverage intervals in a partial spline model
• Smoothing with Split Linear Fits
• Detection, Classification, and Measurement of Discontinuities

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