Quantile regression for lead-time uncertainty

This technical brief treats quantile regression for lead-time uncertainty as a decision system: define its state, objective, feasible actions and evidence before comparing algorithms.

Practitioner lens

The strongest evaluation of quantile regression for lead-time uncertainty compares decision quality with a transparent baseline, preserves time ordering and reports how performance varies by scenario.

First experiment

Compare against a transparent baseline under both routine conditions and deliberately adverse scenarios.

This is an original educational brief. It is a starting point for discussion, not a claim that one technique fits every supply chain.