Proposes FDR-controlling posterior decision rules for signal detection under horseshoe and similar continuous shrinkage priors that attain the optimal detection boundary with asymptotic FDR and FNR control in sparse normal means models.
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Multiple testing with the horseshoe
Proposes FDR-controlling posterior decision rules for signal detection under horseshoe and similar continuous shrinkage priors that attain the optimal detection boundary with asymptotic FDR and FNR control in sparse normal means models.