Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Modelo ARIMA Bayesiano× | Autoregressores Vetoriais (VAR)× | |
|---|---|---|
| Área | Econometria | Econometria |
| Família | Regression model | Regression model |
| Ano de origem≠ | 1970s (ARIMA); Bayesian extension prominent from 1990s | 1980 |
| Autor original≠ | Pole, West & Harrison (Bayesian treatment); Box & Jenkins (ARIMA foundation) | Christopher A. Sims |
| Tipo≠ | Bayesian time series model | Multivariate time-series model |
| Fonte seminal≠ | Pole, A., West, M., & Harrison, J. (1994). Applied Bayesian Forecasting and Time Series Analysis. Chapman & Hall. ISBN: 978-0412416903 | Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1–48. DOI ↗ |
| Outros nomes | Bayesian ARIMA, BARIMA, Bayesian Box-Jenkins model, Bayesian integrated time series model | VAR, VAR model, vector autoregressive model, multivariate autoregression |
| Relacionados≠ | 6 | 5 |
| Resumo≠ | The Bayesian ARIMA model combines the classical Box-Jenkins ARIMA framework with Bayesian inference. Instead of obtaining single point estimates for autoregressive and moving average parameters, it places prior distributions over them and uses observed data to update beliefs into a full posterior distribution, enabling coherent uncertainty quantification and probabilistic 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. |
| ScholarGateConjunto de dados ↗ |
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