FAB-PPI applies frequentist-assisted-by-Bayes confidence regions to the PPI rectifier, yielding shorter asymptotic confidence intervals when predictions are accurate and reverting to standard PPI under a horseshoe prior when they are not.
The marginal likelihood is given by π(y) = Z ∞ −∞ N (y | β, σ2)πHS(β)dβ = 1√ 2πσ 2 Z ∞ 0 1√ 1 + ν2 e − y2 2σ2 (1+ν2 ) p(ν)dν = 2 π √ 2πσ 2 Z ∞ 0 e − y2 2σ2 (1+ν2 ) 1 (1 + ν2)3/2 dν
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
stat.ML 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
FAB-PPI: Frequentist, Assisted by Bayes, Prediction-Powered Inference
FAB-PPI applies frequentist-assisted-by-Bayes confidence regions to the PPI rectifier, yielding shorter asymptotic confidence intervals when predictions are accurate and reverting to standard PPI under a horseshoe prior when they are not.