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stat.ME2026
Studentized Cheap Bootstrap: Achieving Higher-Order Coverage Accuracy with Low Computation
Shengyi He, Henry Lam, Yunhao Yan
The bootstrap is a versatile method for quantifying statistical uncertainty. Among its variants, a popular approach, the studentized bootstrap, provably achieves higher-order cover…
stat.ME2024
Quantifying Distributional Input Uncertainty via Inflated Kolmogorov-Smirnov Confidence Band
Motong Chen, Henry Lam, Zhenyuan Liu
In stochastic simulation, input uncertainty refers to the propagation of the statistical noise in calibrating input models to impact output accuracy, in addition to the Monte Carlo…