Predicting Percentiles#
Forecasting specific percentiles to convey the outcome distribution.
Important
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What it is#
Predicting percentiles means forecasting specific percentiles (quantiles) of the outcome distribution — the value below which a given percentage of outcomes fall — instead of only a single mean. A percentile is a quantile stated as a percent: the 0.9 quantile is the 90th percentile.
Why percentiles#
A handful of percentiles (say the 10th, 50th and 90th) sketch the range of outcomes and their best- and worst-case scenarios, exposing uncertainty and enabling asymmetric decisions — without committing to a parametric distribution.
How it’s done#
Percentiles are produced by quantile regression (and its tree / boosting variants), each trained on the pinball loss for its level; stacking many percentiles approximates the full distribution.
Theme: Risk & Probabilistic Forecasting · All terminology
Hint
Mind map — connected ideas
Quantile Forecasts · Quantile Level · Quantile Regression · Prediction Intervals (PI) · Probabilistic Forecasts · Point Forecasts
Hint
More in Risk & Probabilistic Forecasting
Continuous Probabilistic Forecasts · Continuous Ranked Probability Score (CRPS) · Deterministic forecasts · Full Distribution · Pinball Loss (a.k.a. Quantile Loss) · Point Forecasts · Prediction Intervals (PI) · Probabilistic Forecasts · Probabilistic Scoring · Probability Forecasts · Quantile Forecasts · Quantile Level · Quantile Regression · Return Distribution
See also
Source article Adapted (context, re-expressed) in our own words from: Predicting Percentiles (insightful-data-lab.com).