Adaptivity in convolution models with partially known noise distribution

DOI10.1214/08-EJS225zbMath1320.62066arXiv0804.1056WikidataQ122925493 ScholiaQ122925493MaRDI QIDQ1951778

Cristina Butucea, Catherine Matias, Christophe Pouet

Publication date: 24 May 2013

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

Full work available at URL: https://arxiv.org/abs/0804.1056

zbMATH Keywords

stable lawsgoodness-of-fit testsinfinitely differentiable functionsSobolev classesconvolution modeladaptive nonparametric testspartially known noisequadratic functional estimation

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Nonparametric hypothesis testing (62G10) Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05)

Related Items (7)

Adaptive goodness-of-fit testing from indirect observations ⋮ Sparse covariance matrix estimation in high-dimensional deconvolution ⋮ Deconvolution for some singular density errors via a combinatorial median of means approach ⋮ Density deconvolution in a two-level heteroscedastic model with unknown error density ⋮ Estimation of the Boundary of a Variable Observed With Symmetric Error ⋮ Comment on identification and estimation of nonlinear models using two samples with nonclassical measurement errors ⋮ Frontier estimation in the presence of measurement error with unknown variance

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• On the effect of estimating the error density in nonparametric deconvolution
• Density Estimation for the Case of Supersmooth Measurement Error

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