Bootstrap prediction intervals with asymptotic conditional validity and unconditional guarantees
Bootstrap prediction intervals with asymptotic conditional validity and unconditional guarantees
Abstract It can be argued that optimal prediction should take into account all available data. Therefore, to evaluate a prediction interval’s performance one should employ conditional coverage probability, conditioning on all available observations. Focusing on a linear model, we derive the asymptotic distribution of the difference between the conditional coverage …