A mollifier approach to the deconvolution of probability densities

Cites Work

Unnamed Item
Unnamed Item
Unnamed Item
Unnamed Item
Unnamed Item
Unnamed Item
Unnamed Item
Lower bounds in the convolution structure density model
Comparing parameter choice methods for regularization of ill-posed problems
Structural adaptive deconvolution under \({\mathbb{L}_p}\)-losses
On the optimal rates of convergence for nonparametric deconvolution problems
Deconvolution with unknown error distribution
Density estimation by kernel and wavelets methods: optimality of Besov spaces
A mollification method for ill-posed problems
Adaptive wavelet estimator for nonparametric density deconvolution
Oracle inequalities and adaptive estimation in the convolution structure density model
About the constants in Talagrand's concentration inequalities for empirical processes.
Anisotropic adaptive kernel deconvolution
Ridge-parameter regularization to deconvolution problem with unknown error distribution
On deconvolution with repeated measurements
A ridge-parameter approach to deconvolution
A SPECTRAL METHOD FOR DECONVOLVING A DENSITY
Nonparametric function estimation under Fourier-oscillating noise
Asymptotically Minimax Adaptive Estimation. I: Upper Bounds. Optimally Adaptive Estimates
A mollifier method for linear operator equations of the first kind
Penalized contrast estimator for adaptive density deconvolution
Deconvolving kernel density estimators
Sharp Optimality in Density Deconvolution with Dominating Bias. I
A variational approach to the inversion of truncated Fourier operators
Optimal Rates of Convergence for Deconvolving a Density
Asymptotically Minimax Adaptive Estimation. II. Schemes without Optimal Adaptation: Adaptive Estimators
Density Estimation for the Case of Supersmooth Measurement Error
Geometry of linear ill-posed problems in variable Hilbert scales
Stabilized Reconstruction in Signal and Image Processing
Deconvolution of supersmooth densities with smooth noise
On a Problem of Adaptive Estimation in Gaussian White Noise
Statistical Inverse Estimation in Hilbert Scales
Consistent deconvolution in density estimation
Mathematical Foundations of Infinite-Dimensional Statistical Models
Characterizations of Variational Source Conditions, Converse Results, and Maxisets of Spectral Regularization Methods
Finite sample penalization in adaptive density deconvolution
The Lepskii principle revisited
The Gradient Projection Method under Mild Differentiability Conditions
Methodology for Non-Parametric Deconvolution When the Error Distribution is Unknown
The Identity of Weak and Strong Extensions of Differential Operators
Convex analysis and monotone operator theory in Hilbert spaces

This page was built for publication: A mollifier approach to the deconvolution of probability densities