TARCO corrects measurement-error-induced correlated contamination in tree-aggregated compositional regression via bias-corrected estimating equations, tree-aware PSD stabilization, and sparse regularization, with finite-sample bounds and sign consistency.
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PRADAS derives a Bayes-optimal mirror statistic for any splitting scheme, establishes asymptotic FDR control under weak dependence, and optimizes the split ratio as a stopping time to improve power over standard equal-split methods.
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Tree-aggregated regression for compositional data with measurement errors
TARCO corrects measurement-error-induced correlated contamination in tree-aggregated compositional regression via bias-corrected estimating equations, tree-aware PSD stabilization, and sparse regularization, with finite-sample bounds and sign consistency.
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PRADAS: PRior-Assisted DAta Splitting for False Discovery Rate Control
PRADAS derives a Bayes-optimal mirror statistic for any splitting scheme, establishes asymptotic FDR control under weak dependence, and optimizes the split ratio as a stopping time to improve power over standard equal-split methods.