Methoden vergleichen
Prüfen Sie die ausgewählten Methoden nebeneinander; abweichende Zeilen sind hervorgehoben.
| ARIMA-Modell (Autoregressive Integrated Moving Average)× | Konforme Prädiktion für Zeitreihenprognosen× | |
|---|---|---|
| Fachgebiet | Ökonometrie | Ökonometrie |
| Familie | Regression model | Regression model |
| Entstehungsjahr≠ | 2015 | 2021 |
| Urheber≠ | Box & Jenkins (Box-Jenkins methodology) | Angelopoulos & Bates (tutorial); Xu & Xie (time-series EnbPI) |
| Typ≠ | Univariate time-series model | Distribution-free prediction interval wrapper |
| Wegweisende Quelle≠ | Box, G. E. P., Jenkins, G. M., Reinsel, G. C. & Ljung, G. M. (2015). Time Series Analysis: Forecasting and Control (5th ed.). Wiley. ISBN: 978-1118675021 | Angelopoulos, A. N. & Bates, S. (2023). Conformal Prediction: A Gentle Introduction. Foundations and Trends in Machine Learning, 16(4), 494-591. DOI ↗ |
| Aliasnamen≠ | Box-Jenkins model, ARIMA(p,d,q), ARIMA Modeli | conformal prediction, distribution-free prediction intervals, EnbPI, Konformal Tahmin (Conformal Prediction — Zaman Serisi) |
| Verwandt≠ | 5 | 4 |
| Zusammenfassung≠ | ARIMA is a univariate time-series forecasting model that combines autoregressive, integrated (differencing), and moving-average components to predict a single continuous series from its own past. It is the centrepiece of the Box-Jenkins methodology set out in Box, Jenkins, Reinsel & Ljung's Time Series Analysis (5th ed., 2015). | 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). |
| ScholarGateDatensatz ↗ |
|
|