Deconvolving a density from partially contaminated observations

DOI10.1006/jmva.1995.1078zbMath0863.62037OpenAlexW2000293834MaRDI QIDQ1907821

Christian H. Hesse

Publication date: 15 June 1997

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1006/jmva.1995.1078

zbMATH Keywords

rates of convergencedeconvolutionmeasurement erroridentifiabilitykernel density estimatorscontaminationalmost sure ratescontinuous bounded density

Mathematics Subject Classification ID

Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05)

Related Items (12)

Data-driven deconvolution ⋮ Iterative density estimation from contaminated observations ⋮ Generalized deconvolution estimation by multiwavelets ⋮ A new approach to estimator selection ⋮ Point-wise wavelet estimation in the convolution structure density model ⋮ Oracle inequalities and adaptive estimation in the convolution structure density model ⋮ Optimal iterative density deconvolution ⋮ Well-posedness of measurement error models for self-reported data ⋮ Low Order Approximations in Deconvolution and Regression with Errors in Variables ⋮ Plug-in L₂-upper error bounds in deconvolution, for a mixing density estimate in R^d and for its derivatives, via the L₁-error for the mixture ⋮ Density estimation with contamination: minimax rates and theory of adaptation ⋮ Deconvolving multidimensional density from partially contaminated observations

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