Estimating a concave distribution function from data corrupted with additive noise

DOI10.1214/07-AOS579zbMath1162.62029arXiv0904.0091OpenAlexW3103755183MaRDI QIDQ1020980

Geurt Jongbloed, Frank H. van der Meulen

Publication date: 4 June 2009

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/0904.0091

zbMATH Keywords

asymptotic distributionmaximum likelihoodleast squaresdeconvolutionminimax riskdecreasing density

Mathematics Subject Classification ID

Density estimation (62G07) Asymptotic distribution theory in statistics (62E20) Nonparametric estimation (62G05)

Related Items (6)

Error bounds for spectral enhancement which are based on variable Hilbert scale inequalities ⋮ Inference for Local Parameters in Convexity Constrained Models ⋮ A Bernstein-type estimator for decreasing density with application to \(p\)-value adjustments ⋮ Nonparametric shape-restricted regression ⋮ On testing for local monotonicity in deconvolution problems ⋮ Global rate results for the MLE in a class of deconvolution models

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