On the distribution of the clipping median under a mixture model

DOI10.1016/j.spl.2004.10.016zbMath1058.62018OpenAlexW2047002035MaRDI QIDQ1767744

Ansgar Steland

Publication date: 8 March 2005

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

Full work available at URL: http://hdl.handle.net/2003/20153

zbMATH Keywords

EconometricsChange pointImage processingEdge detectionRobust statisticsJump-preserving estimation

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Nonparametric hypothesis testing (62G10) Image analysis in multivariate analysis (62H35) Exact distribution theory in statistics (62E15)

Related Items (10)

MONITORING PROCEDURES TO DETECT UNIT ROOTS AND STATIONARITY ⋮ Nonlinear Image Processing and Filtering: A Unified Approach Based on Vertically Weighted Regression ⋮ Vertically Weighted Averages in Hilbert Spaces and Applications to Imaging: Fixed-Sample Asymptotics and Efficient Sequential Two-Stage Estimation ⋮ Resampling methods for the nonparametric and generalized Behrens-Fisher problems ⋮ Decoupling change-point detection based on characteristic functions: methodology, asymptotics, subsampling and application ⋮ Estimation of the quantile function using Bernstein–Durrmeyer polynomials ⋮ Asymptotic behavior of RA-estimates in autoregressive 2D processes ⋮ A binary control chart to detect small jumps ⋮ Random Walks with Drift – A Sequential Approach ⋮ On the accuracy of fixed sample and fixed width confidence intervals based on the vertically weighted average

Uses Software

• Mathematica

Cites Work

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• Sequential control of time series by functionals of kernel-weighted empirical processes under local alternatives
• Jump preserving signal reconstruction using vertical weighting.
• Vertically weighted regression -- a tool for constructing control charts
• Edge-Preserving Smoothers for Image Processing
• A nonlinear gaussian filter applied to images with discontinuities
• Jump-preserving monitoring of dependent time series using pilot estimators
• Generalizations of the Glivenko-Cantelli Theorem
• On detecting jumps in time series: nonparametric setting
• On the Convergence of Empiric Distribution Functions

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