Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| ARIMA (autoregresīvais integrētais slīdošā vidējā) modelis× | Pārtraukto laika sēriju (ITS) analīze× | |
|---|---|---|
| Nozare≠ | Ekonometrija | Cēloņsakarību secināšana |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 2015 | 2002 |
| Autors≠ | Box & Jenkins (Box-Jenkins methodology) | Wagner, Soumerai, Zhang & Ross-Degnan (segmented regression); Bernal, Cummins & Gasparrini (tutorial) |
| Tips≠ | Univariate time-series model | Quasi-experimental segmented regression |
| 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 | Bernal, J. L., Cummins, S., & Gasparrini, A. (2017). Interrupted time series regression for the evaluation of public health interventions: a tutorial. International Journal of Epidemiology, 46(1), 348-355. DOI ↗ |
| Citi nosaukumi | Box-Jenkins model, ARIMA(p,d,q), ARIMA Modeli | ITS analysis, segmented regression of time series, Kesintili Zaman Serisi (ITS) Analizi |
| Saistītās | 5 | 5 |
| Kopsavilkums≠ | 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). | Interrupted Time Series analysis is a quasi-experimental design that estimates the effect of a single, well-dated intervention by comparing the trajectory of an outcome before and after it occurs. Formalised as segmented regression by Wagner and colleagues (2002) and popularised as a public-health evaluation tutorial by Bernal, Cummins and Gasparrini (2017), it separates the intervention's impact into a change in level and a change in slope. |
| ScholarGateDatu kopa ↗ |
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