Leave a Window Out: Modifying the Jackknife for Predictive Inference in Time Series

ArXi:2605.30292v1 Announce Type: cross Conformal prediction methods enjoy strong theoretical and empirical predictive inference performance, provided the data is exchangeable, and predictors are trained in a memoryless fashion. However, these assumptions and constraints are impractical in many real-data settings, such as time series (where temporal dependence violates exchangeability, and where memoryless predictors will inevitably have poor predictive accuracy