Deprecated: $wgMWOAuthSharedUserIDs=false is deprecated, set $wgMWOAuthSharedUserIDs=true, $wgMWOAuthSharedUserSource='local' instead [Called from MediaWiki\HookContainer\HookContainer::run in /var/www/html/w/includes/HookContainer/HookContainer.php at line 135] in /var/www/html/w/includes/Debug/MWDebug.php on line 372
Asymptotic Bayes-optimality under sparsity of some multiple testing procedures - MaRDI portal

Asymptotic Bayes-optimality under sparsity of some multiple testing procedures

From MaRDI portal
Publication:638803

DOI10.1214/10-AOS869zbMath1221.62012arXiv1002.3501MaRDI QIDQ638803

Jayanta K. Ghosh, Florian Frommlet, Małgorzata Bogdan, Arijit Chakrabarti

Publication date: 14 September 2011

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1002.3501



Related Items

The Indian official statistical system revisited, Bayesian variable selection in quantile regression with random effects: an application to Municipal Human Development Index, Testing un-separated hypotheses by estimating a distance, On the d-posterior approach to the multiple testing problem, False Discovery Rate Smoothing, Group SLOPE – Adaptive Selection of Groups of Predictors, Bayesian Approaches to Shrinkage and Sparse Estimation, Horseshoe Regularisation for Machine Learning in Complex and Deep Models1, Optimal false discovery control of minimax estimators, Some permutation symmetric multiple hypotheses testing rules under dependent setup, SLOPE-adaptive variable selection via convex optimization, Bayes multiple decision functions, Some optimality properties of FDR controlling rules under sparsity, Asymptotic Bayes-optimality under sparsity of some multiple testing procedures, Frequentist properties of Bayesian multiplicity control for multiple testing of normal means, Global-local mixtures: a unifying framework, Empirical priors and coverage of posterior credible sets in a sparse normal mean model, On the asymptotic properties of SLOPE, On spike and slab empirical Bayes multiple testing, Asymptotically minimax empirical Bayes estimation of a sparse normal mean vector, Binary classification with pFDR‐pFNR losses, Modified versions of the Bayesian information criterion for sparse generalized linear models, Large-scale multiple hypothesis testing with the normal-beta prime prior, A survey of nonparametric mixing density estimation via the predictive recursion algorithm, Model selection with mixed variables on the Lasso path, The horseshoe-like regularization for feature subset selection, Lasso meets horseshoe: a survey, On the power of some sequential multiple testing procedures, On false discovery rate thresholding for classification under sparsity, Sparse portfolio selection via Bayesian multiple testing, On the role of the prior in multiplicity adjustment, Sparse linear mixed model selection via streamlined variational Bayes, Classes of multiple decision functions strongly controlling FWER and FDR, Higher criticism for large-scale inference, especially for rare and weak effects



Cites Work