Structural adaptive deconvolution under \({\mathbb{L}_p}\)-losses
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Publication:726580
DOI10.3103/S1066530716010026zbMath1342.62054arXiv1504.06246MaRDI QIDQ726580
Publication date: 12 July 2016
Published in: Mathematical Methods of Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1504.06246
deconvolutiondensity estimationkernel estimatoradaptationconcentration inequalityoracle inequalityindependence structure
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Cites Work
- Unnamed Item
- Unnamed Item
- Anisotropic de-noising in functional deconvolution model with dimension-free convergence rates
- Multivariate density estimation under sup-norm loss: oracle approach, adaptation and independence structure
- Upper functions for positive random functionals. I: General setting and Gaussian random functions
- On adaptive minimax density estimation on \(\mathbb R^d\)
- Lower bounds in the convolution structure density model
- Adaptive estimation of linear functionals in the convolution model and applications
- Bandwidth selection in kernel density estimation: oracle inequalities and adaptive minimax optimality
- Uniform bounds for norms of sums of independent random functions
- Adaptively local one-dimensional subproblems with application to a deconvolution problem
- Strong consistency and rates for deconvolution of multivariate densities of stationary processes
- On the optimal rates of convergence for nonparametric deconvolution problems
- Concentration inequalities and model selection. Ecole d'Eté de Probabilités de Saint-Flour XXXIII -- 2003.
- Pointwise adaptive estimation of a multivariate density under independence hypothesis
- Optimal bandwidth selection for multivariate kernel deconvolution density estimation
- Structural adaptation via \(\mathbb L_p\)-norm oracle inequalities
- Nonparametric estimation of composite functions
- Rates of convergence of some estimators in a class of deconvolution problems
- Nonasymptotic universal smoothing factors, kernel complexity and Yatracos classes
- Adaptive wavelet estimator for nonparametric density deconvolution
- Adaptive density estimation in the pile-up model involving measurement errors
- Anisotropic adaptive kernel deconvolution
- \(\mathbb{L}_{p}\) adaptive estimation of an anisotropic density under independence hypothesis
- Global uniform risk bounds for wavelet deconvolution estimators
- Estimating composite functions by model selection
- Adaptive estimation under single-index constraint in a regression model
- A ridge-parameter approach to deconvolution
- Rate-optimal estimation for a general class of nonparametric regression models with unknown link functions
- Multivariate probability density deconvolution for stationary random processes
- Deconvolving kernel density estimators
- Classical Fourier Analysis
- Sharp Optimality in Density Deconvolution with Dominating Bias. I
- Sharp Optimality in Density Deconvolution with Dominating Bias. II
- Optimal Rates of Convergence for Deconvolving a Density
- Deconvolution of supersmooth densities with smooth noise
- Non-Parametric Confidence Bands in Deconvolution Density Estimation
- Deconvolution from Fourier-oscillating error densities under decay and smoothness restrictions
- Introduction to nonparametric estimation
- Nonlinear estimation in anisotropic multi-index denoising
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