Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| ARMA modelis (Autoregresīvs vidējais aritmētiskais)× | Vektora autoregresija (VAR)× | |
|---|---|---|
| Nozare | Ekonometrija | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1970 | 1980 |
| Autors≠ | George E. P. Box and Gwilym M. Jenkins | Christopher A. Sims |
| Tips≠ | Time series model | Multivariate time-series model |
| Pirmavots≠ | Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day. link ↗ | Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1–48. DOI ↗ |
| Citi nosaukumi | ARMA, Box-Jenkins model, autoregressive moving average, AR(p)MA(q) | VAR, VAR model, vector autoregressive model, multivariate autoregression |
| Saistītās | 5 | 5 |
| Kopsavilkums≠ | The ARMA(p,q) model describes a stationary time series as a combination of two components: an autoregressive part that regresses the current value on its own past p values, and a moving average part that accounts for past q error terms. It is the foundational framework of the Box-Jenkins methodology for univariate time series modelling and short-run forecasting. | Vector Autoregression is a multivariate time-series model in which each variable is regressed on its own lags and the lags of all other variables in the system. Originally proposed by Sims (1980) as a data-driven alternative to large structural macroeconomic models, VAR has become the standard workhorse for dynamic analysis in empirical economics and finance. |
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