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.
Journal of the Royal Statistical Society Series B: Statistical Methodology , volume=
3 Pith papers cite this work. Polarity classification is still indexing.
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A new statistical method integrates database priors into conditional GGMs via a structured weighted penalty for improved population-level and context-specific PPI network reconstruction, validated in simulations and UK Biobank cardiometabolic proteomics data.
MDS screens assets using Fréchet variation dependence on weighted point-curve objects of returns and intraday risk, then applies standard allocation, with claimed consistency guarantees and better out-of-sample performance on Chinese high-frequency stock data.
citing papers explorer
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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.
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Prior-informed conditional Gaussian graphical models: an application to protein interaction network reconstruction
A new statistical method integrates database priors into conditional GGMs via a structured weighted penalty for improved population-level and context-specific PPI network reconstruction, validated in simulations and UK Biobank cardiometabolic proteomics data.
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Large-Scale Asset Selection via Metric Dependence with Enriched High Frequency Information
MDS screens assets using Fréchet variation dependence on weighted point-curve objects of returns and intraday risk, then applies standard allocation, with claimed consistency guarantees and better out-of-sample performance on Chinese high-frequency stock data.