Local Posterior Concentration Rate for Multilevel Sparse Sequences

DOI10.1007/978-3-319-54084-9_6zbMath1364.62060OpenAlexW2607836122MaRDI QIDQ5267855

Eduard Belitser, Nurzhan Nurushev

Publication date: 13 June 2017

Published in: Springer Proceedings in Mathematics & Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-319-54084-9_6

zbMATH Keywords

empirical Bayesian approachlocal posterior concentration ratemultilevel sparse sequences

Mathematics Subject Classification ID

Parametric hypothesis testing (62F03) Bayesian inference (62F15)

Related Items

Empirical priors and coverage of posterior credible sets in a sparse normal mean model ⋮ Data-driven priors and their posterior concentration rates ⋮ Uncertainty quantification for robust variable selection and multiple testing

Uses Software

• EBayesThresh

Cites Work

• Unnamed Item
• The horseshoe estimator: posterior concentration around nearly black vectors
• Minimax risk over \(l_ p\)-balls for \(l_ q\)-error
• Needles and straw in haystacks: Empirical Bayes estimates of possibly sparse sequences
• Needles and straw in a haystack: posterior concentration for possibly sparse sequences
• On optimality of Bayesian testimation in the normal means problem
• Adapting to unknown sparsity by controlling the false discovery rate
• Ideal spatial adaptation by wavelet shrinkage
• Gaussian model selection

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