A comparison of some conformal quantile regression methods

Understand

We compare two recently proposed methods that combine ideas from conformal inference and quantile regression to produce locally adaptive and marginally valid prediction intervals under sample exchangeability (Romano et al., 2019; Kivaranovic et al., 2019).

• First, we prove that these two approaches are asymptotically efficient in large samples, under some additional assumptions.
• Then we compare them empirically on simulated and real data.
• Our results demonstrate that the method in Romano et al.