Distribution-Free Prediction Intervals Under Covariate Shift, With an Application to Causal Inference
协变量分布迁移下的分布无关预测区间及因果推断应用
Owing to its appealing distribution-free feature, conformal inference has become a popular tool for constructing prediction intervals with a desired coverage rate. In scenarios involving covariate shift, where the shift function needs to be estimated from data, many existing methods resort to data-splitting techniques. However, these approaches often lead to wider intervals and less reliable coverage rates, especially when dealing with finite sample sizes. To address these…