Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Bayes SARIMA modelis× | SARIMA modelis× | |
|---|---|---|
| Nozare | Ekonometrija | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1970s–1990s | 1970 (first edition); 1976 (revised) |
| Autors≠ | Box & Jenkins (classical SARIMA); Bayesian extensions developed through Zellner, Geweke, and later MCMC-era researchers | Box, Jenkins, and Reinsel |
| Tips≠ | Bayesian time-series model | Seasonal time series model |
| Pirmavots≠ | 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 | Box, G. E. P., Jenkins, G. M., & Reinsel, G. C. (1976). Time Series Analysis: Forecasting and Control (revised ed.). Holden-Day. ISBN: 978-0130607744 |
| Citi nosaukumi | Bayesian SARIMA, Bayesian seasonal ARIMA, BSARIMA, Bayesian seasonal time-series model | SARIMA, seasonal ARIMA, Box-Jenkins seasonal model, ARIMA with seasonal component |
| Saistītās≠ | 4 | 5 |
| Kopsavilkums≠ | The Bayesian SARIMA model combines the classical Box-Jenkins Seasonal ARIMA framework with Bayesian inference to handle seasonal time-series data. Rather than producing a single point estimate, it yields a full posterior distribution over model parameters, propagating parameter uncertainty directly into forecasts and enabling principled incorporation of prior knowledge. | SARIMA extends ARIMA by adding seasonal autoregressive and moving-average operators to capture repeating patterns at fixed intervals — such as monthly, quarterly, or annual cycles. Denoted SARIMA(p,d,q)(P,D,Q)s, it is the standard workhorse for univariate seasonal time series forecasting in econometrics, economics, and official statistics. |
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