Deconvolution model with fractional Gaussian noise: a minimax study

DOI10.1016/J.SPL.2016.05.022zbMath1366.62058OpenAlexW2434806141MaRDI QIDQ310673

Rida Benhaddou

Publication date: 8 September 2016

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.spl.2016.05.022

zbMATH Keywords

deconvolutionfractional Gaussian noiseminimax convergence rate

Mathematics Subject Classification ID

Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05) Fractional processes, including fractional Brownian motion (60G22)

Related Items (5)

Minimax lower bounds for the simultaneous wavelet deconvolution with fractional Gaussian noise and unknown kernels ⋮ Laplace deconvolution with dependent errors: a minimax study ⋮ Blind deconvolution model in periodic setting with fractional Gaussian noise ⋮ Anisotropic functional deconvolution for the irregular design: A minimax study ⋮ Estimation in nonparametric regression model with additive and multiplicative noise via Laguerre series

Cites Work

• Wavelet regression in random design with heteroscedastic dependent errors
• Minimax estimation via wavelets for indirect long-memory data
• Nonlinear solution of linear inverse problems by wavelet-vaguelette decomposition
• Wavelet deconvolution in a periodic setting with long-range dependent errors
• Multichannel deconvolution with long range dependence: upper bounds on the \(L^p\)-risk \((1 \leq p < \infty)\)
• Multichannel deconvolution with long-range dependence: a minimax study
• Aggregation for Gaussian regression
• Wavelet Deconvolution in a Periodic Setting

This page was built for publication: Deconvolution model with fractional Gaussian noise: a minimax study