Method evidence record
Conformal Prediction (Time Series)
Conformal prediction is a distribution-free wrapper that turns any point forecaster — ARIMA, a neural network, or a machine-learning model — into valid prediction intervals using only its residuals. The time-series form was popularised by Xu & Xie (2021) and the modern tutorial treatment by Angelopoulos & Bates (2023).
Source record
Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.
Conformal Prediction for Time-Series Forecasting
Taxonomic method record · regression-model / econometrics
- Angelopoulos, A. N. & Bates, S. (2023). Conformal Prediction: A Gentle Introduction. Foundations and Trends in Machine Learning, 16(4), 494-591. · DOI 10.1561/2200000101
- Xu, C. & Xie, Y. (2021). Conformal Prediction Interval for Dynamic Time-Series. International Conference on Machine Learning (ICML). · URL
Curated claims
Claims persisted in the evidence ledger, each with its own assessment.
No curated claims yet
This view does not invent a claim assessment when the ledger has none.
Related methods
Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.