Vector Autoregression Algorithm
Jump to navigation
Jump to search
See: Autoregression Algorithm, Multivariate Dataset, Multi-Predictor Forecasting Algorithm, ARIMA, Bayesian Vector Autoregression.
References
2013
- http://en.wikipedia.org/wiki/Vector_autoregression
- Vector autoregression (VAR) is a statistical model used to capture the linear interdependencies among multiple time series. VAR models generalize the univariate autoregression (AR) models by allowing for more than one evolving variable. All variables in a VAR are treated symmetrically in a structural sense (although the estimated quantitative response coefficients will not in general be the same); each variable has an equation explaining its evolution based on its own lags and the lags of the other model variables. VAR modeling does not require as much knowledge about the forces influencing a variable as do structural models with simultaneous equations: The only prior knowledge required is a list of variables which can be hypothesized to affect each other intertemporally.