A statistical model called vector auto regression (VAR) is used to capture the relationship between numerous quantities as they change over time. A stochastic process model, or VAR, is a form of stochastic process model. By allowing for multivariate time series, VAR models extend the single-variable (univariate) autoregressive model. In economics and natural science, VAR models are frequently utilised. Each variable, like the autoregressive model, has an equation that models its progression through time. The lagged (past) values of the variable, the lagged values of the other variables in the model, and an error term are all included in this equation.