3 papers
stat.ME2026
Higher Order Risk Comparisons of Oracle Calibrated Global Local Priors
Dongu Han
First-order minimaxity offers limited guidance for choosing among global-local shrinkage priors, since different local-tail distributions can yield the same leading risk. Compariso…
stat.ME2026
Log-regularly varying scale mixture of asymmetric Laplaces for robust Bayesian quantile regression
Dongu Han, Genya Kobayashi, Shonosuke Sugasawa
Bayesian quantile regression based on the asymmetric Laplace (AL) distribution can be sensitive to extreme observations because of its exponentially decaying tails. We propose a ro…
stat.ME2026
Dynamic Bayesian regression quantile synthesis for forecasting outlook-at-risk
Genya Kobayashi, Shonosuke Sugasawa, Yuta Yamauchi +1
This paper proposes dynamic Bayesian regression quantile synthesis (DRQS), a novel method for quantile forecasting within the Bayesian predictive synthesis (BPS) framework designed…