Conformalized Regression for Continuous Bounded Outcomes

Excerpt

arXiv:2507.14023v3 Announce Type: replace-cross Abstract: Regression problems with continuous bounded outcomes frequently arise in statistical and machine learning applications, such as the analysis of rates and proportions. A central challenge in this setting is predicting the response at a new covariate value. Most of the existing literature has focused either on point prediction or on interval prediction based on asymptotic approximations. We develop conformal prediction intervals for bounded