Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| SARIMA (ARIMA Sezonier)× | Profet× | |
|---|---|---|
| Domeniu | Econometrie | Econometrie |
| Familie | Regression model | Regression model |
| Anul apariției≠ | 2015 | 2018 |
| Autorul original≠ | Box & Jenkins (seasonal extension of ARIMA) | Taylor & Letham (Facebook/Meta) |
| Tip≠ | Seasonal time-series model | Decomposable (structural) time series model |
| Sursa seminală≠ | 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 | Taylor, S. J. & Letham, B. (2018). Forecasting at Scale. The American Statistician, 72(1), 37-45. DOI ↗ |
| Denumiri alternative≠ | seasonal ARIMA, Box-Jenkins seasonal model, SARIMA — Mevsimsel ARIMA | Prophet, Facebook Prophet, Meta Prophet, forecasting at scale |
| Înrudite | 5 | 5 |
| Rezumat≠ | SARIMA is a seasonal extension of the Box-Jenkins ARIMA model that adds seasonal differencing and seasonal autoregressive and moving-average terms. Developed within the Box, Jenkins, Reinsel and Ljung framework (5th edition, 2015), it forecasts series whose pattern repeats on a yearly, monthly, or weekly period. | Prophet is a Bayesian structural time series model introduced by Taylor and Letham at Facebook/Meta in 2018. It forecasts a continuous series by decomposing it into separate, interpretable trend, seasonality, and holiday components, and is designed to be approachable for analysts working at scale. |
| ScholarGateSet de date ↗ |
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