Convergence Rates for Linear Inverse Problems in the Presence of an Additive Normal Noise

DOI10.1080/07362990802558295zbMath1165.65020OpenAlexW2092727037MaRDI QIDQ3625460

Andreas Hofinger, Hanna K. Pikkarainen

Publication date: 5 May 2009

Published in: Stochastic Analysis and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/07362990802558295

zbMATH Keywords

convergenceTikhonov regularizationlinear inverse problemsBayesian frameworkparameter choice rulesConvergence ratesKy Fan metricadditive normal noisestatistical inversion theories

Mathematics Subject Classification ID

Numerical computation of eigenvalues and eigenvectors of matrices (65F15) Ill-posedness and regularization problems in numerical linear algebra (65F22) Convergence of probability measures (60B10)

Related Items (4)

Regularized Posteriors in Linear Ill-Posed Inverse Problems ⋮ Quasi-Bayesian analysis of nonparametric instrumental variables models ⋮ A Bayesian inference approach to the ill-posed Cauchy problem of steady-state heat conduction ⋮ REGULARIZING PRIORS FOR LINEAR INVERSE PROBLEMS

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