Asymptotic properties of Bayes risk of a general class of shrinkage priors in multiple hypothesis testing under sparsity

DOI10.1214/15-BA973zbMath1359.62309arXiv1310.7462MaRDI QIDQ516509

Prasenjit Ghosh, Xueying Tang, Arijit Chakrabarti, Malay Ghosh

Publication date: 14 March 2017

Published in: Bayesian Analysis (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1310.7462

zbMATH Keywords

horseshoe empirical Bayes asymptotic optimality Bayes oracle generalized double Pareto normal-exponential-gamma Strawderman-Berger three parameter beta

Mathematics Subject Classification ID

Ridge regression; shrinkage estimators (Lasso) (62J07) Bayesian problems; characterization of Bayes procedures (62C10) Paired and multiple comparisons; multiple testing (62J15)

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The adaptive normal-hypergeometric-inverted-beta priors for sparse signals ⋮ High-dimensional multivariate posterior consistency under global-local shrinkage priors ⋮ Horseshoe Regularisation for Machine Learning in Complex and Deep Models¹ ⋮ A global-local approach for detecting hotspots in multiple-response regression ⋮ Prediction risk for the horseshoe regression ⋮ Large-scale multiple hypothesis testing with the normal-beta prime prior ⋮ Lasso meets horseshoe: a survey ⋮ Modeling Random Effects Using Global–Local Shrinkage Priors in Small Area Estimation ⋮ Revisiting Jeffreys’ Example: Bayes Test of the Normal Mean

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