Empirical Bayes approach to wavelet regression using ϵ-contaminated priors

DOI10.1080/00949650310001643162zbMath1052.62006OpenAlexW2098824552WikidataQ58852381 ScholiaQ58852381MaRDI QIDQ4826345

Theofanis Sapatinas, Claudia Angelini

Publication date: 11 November 2004

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949650310001643162

zbMATH Keywords

wavelet transformsimulationsatomic force microscopy\(\varepsilon\)-contaminated priorswavelet shrinkage estimationexact risk analysistype-II maximum likelihood priors

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Numerical methods for wavelets (65T60) Empirical decision procedures; empirical Bayes procedures (62C12)

Related Items (2)

Larger posterior mode wavelet thresholding and applications ⋮ Frequentist optimality of Bayesian wavelet shrinkage rules for Gaussian and non-Gaussian noise

Cites Work

• Robust Bayes and empirical Bayes analysis with \(\epsilon\)-contaminated priors
• Wavelets, approximation, and statistical applications
• Adapting to Unknown Smoothness via Wavelet Shrinkage
• A theory for multiresolution signal decomposition: the wavelet representation
• Testing a Point Null Hypothesis: The Irreconcilability of P Values and Evidence
• Nonlinear Wavelet Shrinkage with Bayes Rules and Bayes Factors
• Multiple shrinkage and subset selection in wavelets
• Wavelet Thresholding via A Bayesian Approach
• Ideal spatial adaptation by wavelet shrinkage
• Understanding WaveShrink: variance and bias estimation
• Adaptive Bayesian Wavelet Shrinkage
• Wavelet-based image estimation: an empirical Bayes approach using Jeffrey's noninformative prior
• Flexible Empirical Bayes Estimation for Wavelets
• Posterior Probability Intervals for Wavelet Thresholding

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