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

statistics and econometrics, Bayesian vector autoregression (BVAR) uses Bayesian methods to estimate a vector autoregression (VAR) model. BVAR differs with standard...

model is a special case of the vector autoregressive model, the computation of the impulse response in vector autoregression#impulse response applies here...

a vector space as a codomain Vectorization (mathematics), a linear transformation that converts a matrix into a column vector Vector autoregression, an...

normal distribution to higher dimensions. One definition is that a random vector is said to be k-variate normally distributed if every linear combination...

The evolution of a k×1 random vector X {\displaystyle \mathbf {X} } through time can be modelled as a vector autoregression (VAR) as follows: X t = c +...

expectations. A similar test involving more variables can be applied with vector autoregression. The validity of the Granger causality test has been challenged...

stationary stochastic process in terms of two polynomials, one for the autoregression (AR) and the second for the moving average (MA). The general ARMA model...

mean and the covariance matrix of the random vector X {\displaystyle \textstyle \mathbf {X} } , a vector whose jth element ( j = 1 , … , K ) {\displaystyle...

is a vector norm: C = ‖ V − 1 m ‖ = ( m T V − 1 V − 1 m ) 1 / 2 {\displaystyle C=\|V^{-1}m\|=(m^{\mathsf {T}}V^{-1}V^{-1}m)^{1/2}} and the vector m, m...