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Bayesiansk ARIMA-modell×Vektorautoregression (VAR)×
ÄmnesområdeEkonometriEkonometri
FamiljRegression modelRegression model
Ursprungsår1970s (ARIMA); Bayesian extension prominent from 1990s1980
UpphovspersonPole, West & Harrison (Bayesian treatment); Box & Jenkins (ARIMA foundation)Christopher A. Sims
TypBayesian time series modelMultivariate time-series model
UrsprungskällaPole, A., West, M., & Harrison, J. (1994). Applied Bayesian Forecasting and Time Series Analysis. Chapman & Hall. ISBN: 978-0412416903Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1–48. DOI ↗
AliasBayesian ARIMA, BARIMA, Bayesian Box-Jenkins model, Bayesian integrated time series modelVAR, VAR model, vector autoregressive model, multivariate autoregression
Närliggande65
SammanfattningThe 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.
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ScholarGateJämför metoder: Bayesian ARIMA model · Vector Autoregression. Hämtad 2026-06-15 från https://scholargate.app/sv/compare