Multivariate Time series using Vector Autoregression (VAR)

#datascience #machinelearning #timeseries
Detailed video on ADF test - • Time Series Non Statio...
Detailed video on granger causality - • Granger Causality Stat...
You can watch my entire time series here - • Time Series Modelling ...
Vector autoregression (VAR) is a statistical model used to capture the relationship between multiple quantities as they change over time
VAR models (vector autoregressive models) are used for multivariate time series. The structure is that each variable is a linear function of past lags of itself and past lags of the other variables
The Granger causality test is a statistical hypothesis test for determining whether one time series is useful in forecasting another
The Augmented Dickey Fuller Test (ADF) is unit root test for stationarity. Unit roots can cause unpredictable results in your time series analysis.