E. Brunner

Beyond exact and asymptotic: optimization-based tuning of confidence intervals for proportions

Confidence interval estimation for binomial proportions remains challenging in finite samples due to the discreteness of the data, which induces oscillatory coverage behavior. Classical intervals are often conservative (e.g., Clopper–Pearson) or may exhibit undercoverage (e.g., Wald), and exact nominal coverage cannot...