View source: R/BigVARSupportFunctions.R
MultVarSim | R Documentation |
Simulate a VAR
MultVarSim(k, A1, p, Sigma, T)
k |
Number of Series |
A1 |
Either a k \times k coefficient matrix or a kp \times kp matrix created using |
p |
Maximum Lag Order |
Sigma |
Residual Covariance Matrix of dimension k\times k |
T |
Number of simulations |
Returns a T \times k of realizations from a VAR.
Lutkepohl, 'A New Introduction to Multiple Time Series Analysis'
VarptoVar1MC
k=3;p=6 B=matrix(0,nrow=k,ncol=p*k) A1<- matrix(c(.4,-.02,.01,-.02,.3,.02,.01,.04,.3),ncol=3,nrow=3) A2 <- matrix(c(.2,0,0,0,.3,0,0,0,.13),ncol=3,nrow=3) B[,1:k]=A1 B[,(4*k+1):(5*k)]=A2 A <- VarptoVar1MC(B,p,k) Y <-MultVarSim(k,A,p,.1*diag(k),100)
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