3 papers
stat.ME2026
Bayesian Quantile Deep Echo State Networks for Nonlinear Time Series
Antonio De Leon, Raquel Prado, Bruno Sansó
Conditional quantiles are central to asymmetric decision losses, tail-risk assessment, and interval forecasts, but Bayesian quantile regression for nonlinear time series can be dif…
stat.ME2026
Mean-Tilted Intervals: Short Tolerance Intervals
Antonio De Leon, Raquel Prado, Bruno Sansó
Intervals with the same probability content can have different endpoint placements and widths. This matters for tolerance inference, where a reported interval must also satisfy a r…
stat.AP2026
Bayesian Quantile-Based Correction and Synthesis of Hydrologic Products
Antonio De Leon, Raquel Prado, Bruno Sansó
River-flow forecasting requires predictive distributions that remain informative in both routine and extreme conditions. We develop a Bayesian quantile-based correction-and-synthes…