Vector autoregression (VAR) is a statistical model used to capture the relationship between multiple quantities as they change over time. VAR is a type of stochastic process model.

It is a natural extension of the univariate autoregressive model to dynamic mul-tivariate time series. The VAR model has proven to be especially useful for describing the dynamic behavior …

May 14, 2025 · Introduction to VAR What is a VAR Model? Vector Autoregression (VAR) models are a cornerstone in multivariate time series analysis. In a VAR, each variable in the system is …

A vector autoregression (VAR) model is a multivariate time series model containing a system of n equations of n distinct, stationary response variables as linear functions of lagged responses …

Oct 20, 2023 · Whenever you want to estimate a model for multiple time series, the Vector Autoregression (VAR) model will serve you well. This model is suitable for handling multiple …

Aug 31, 2018 · An intuitive introduction to the concept of vector autoregression (VAR). The focus is less on the math behind the method and more on its application in R using the vars package.

May 14, 2024 · Vector Autoregression (VAR) is a multivariate extension of autoregression (AR) models. While traditional AR models analyze the relationship between a single variable and its …

Vector Autoregression (VAR) is a forecasting algorithm that can be used when two or more time series influence each other. That is, the relationship between the time series involved is bi …

Mar 19, 2025 · The Vector Autoregression or VAR model is an essential tool in time series analysis. It is an extension of the univariate autoregressive models and can incorporate …

Feb 6, 2025 · VAR establishes lead-lag relationships and is useful to decide whether one variable is significant in forecasting the other variable. This How-to Guide describes when to apply VAR …