Introduced on day 26
Conformal prediction
A procedure that turns a point forecaster and held-out errors into intervals with finite-sample marginal coverage, assuming calibration and future errors are exchangeable.
In detail
In the split version, a calibration set that the model was not fitted on provides absolute errors; the band is the point forecast plus and minus their (1 - alpha) empirical quantile with a small finite-sample correction. It makes no distributional assumption about the errors, but time series seasonality, drift and regime shifts violate exchangeability, which is why weighted and adaptive variants exist.