Limiting FDP and TPP conjecture for TPoP and CPoP

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Let Assumption hold. In the scalar model, let Φ=P(Y;Π,τ⋆)\Phi={\mathcal P}(Y;\Pi,\tau_\star) be the local false-discovery rate, where (β0,Φ)(\beta_0,\Phi) has the joint distribution induced by the scalar model. For a threshold t∈[0,1]t\in[0,1] and tuning parameter λ\lambda, let t⋆(λ)t_\star(\lambda) be

t⋆(λ)=arg⁡ max⁡⁡t∈[0,1](P(Φ<t)−(1−λ(1−π0)P(Φ<t))E[Φ 1{Φ<t}]).t_\star(\lambda)=\operatorname*{\arg\,\max}_{t\in[0,1]}\left(\mathbb{P}(\Phi<t)-\left(1-\frac{\lambda(1-\pi_0)}{\mathbb{P}(\Phi<t)}\right)\mathbb{E}\left[\Phi\,\mathsf{1}\{\Phi<t\}\right]\right).

Limiting FDP and TPP conjecture. The limiting false discovery proportion and true positive proportion of TPoP satisfy

lim⁡d→∞, n/d→δFDP⁡(TP( ⋅ ;t))=P(β0=0∣Φ<t),\lim_{d\to\infty,\,n/d\to\delta}\operatorname{FDP}(\boldsymbol T_P(\,\cdot\,;t))=\mathbb{P}(\beta_0=0\mid\Phi<t), lim⁡d→∞, n/d→δTPP⁡(TP( ⋅ ;t))=P(Φ<t∣β0≠0),\lim_{d\to\infty,\,n/d\to\delta}\operatorname{TPP}(\boldsymbol T_P(\,\cdot\,;t))=\mathbb{P}(\Phi<t\mid\beta_0\neq0),

and the limiting false discovery proportion and true positive proportion of CPoP satisfy

lim⁡d→∞, n/d→δFDP⁡(CP( ⋅ ;λ))=P(β0=0∣Φ<t⋆(λ)),\lim_{d\to\infty,\,n/d\to\delta}\operatorname{FDP}(\boldsymbol C_P(\,\cdot\,;\lambda))=\mathbb{P}(\beta_0=0\mid\Phi<t_\star(\lambda)), lim⁡d→∞, n/d→δTPP⁡(CP( ⋅ ;λ))=P(Φ<t⋆(λ)∣β0≠0).\lim_{d\to\infty,\,n/d\to\delta}\operatorname{TPP}(\boldsymbol C_P(\,\cdot\,;\lambda))=\mathbb{P}(\Phi<t_\star(\lambda)\mid\beta_0\neq0).

These formulas are suggested by a heuristic replica calculation linking the joint empirical distribution of (β0,j,Pj(D))(\beta_{0,j},P_j(\mathcal D)) to the scalar model; proving the conjecture remains open.

References

Primary source

Taejoo Ahn, Licong Lin and Song Mei, “Near-optimal multiple testing in Bayesian linear models with finite-sample FDR control”, arXiv:2211.02778 (2023).

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