Data-driven boundary estimation in deconvolution problems
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Publication:959284
DOI10.1016/j.csda.2005.02.012zbMath1445.62068OpenAlexW2091321447MaRDI QIDQ959284
Aurore Delaigle, Irène Gijbels
Publication date: 11 December 2008
Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.csda.2005.02.012
bandwidthdensity estimationendpointsdiscontinuity pointsdeconvolution problemboundary pointsdata-driven procedurediagnostic function
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Uses Software
Cites Work
- On the optimal rates of convergence for nonparametric deconvolution problems
- Practical bandwidth selection in deconvolution kernel density estimation
- Kernel-type estimators of jump points and values of a regression function
- On the estimation of jump points in smooth curves
- Bootstrap bandwidth selection in kernel density estimation from a contaminated sample
- Deconvolving kernel density estimators
- Optimal Rates of Convergence for Deconvolving a Density
- Deconvolution with supersmooth distributions
- Estimating a Changepoint, Boundary, or Frontier in the Presence of Observation Error
- Estimation of Integrated Squared Density Derivatives from a Contaminated Sample
- Estimation non paramétrique d'une discontinuité dans une densité
- Bootstrap test for change-points in nonparametric regression
- Boundary bias correction for nonparametric deconvolution
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