MTS: FEVdec – R documentation

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FEVdec

Forecast Error Variance Decomposition

Computes the forecast error variance decomposition of a VARMA model

FEVdec(Phi, Theta, Sig, lag = 4)

`Phi`	VAR coefficient matrices in the form Phi=[Phi1, Phi2, ..., Phip], a k-by-kp matrix.
`Theta`	VMA coefficient matrices in form form Theta=[Theta1, Theta2, ..., Thetaq], a k-by-kq matrix.
`Sig`	The residual covariance matrix Sigma, a k-by-k positive definite matrix.
`lag`	The number of lags of forecast errors variance to be computed. Default is 4.

Use the psi-weight matrices to compute the forecast error covariance and use Cholesky decomposition to perform the decomposition

`irf`	Impulse response matrices
`orthirf`	Orthogonal impulse response matrices
`Omega`	Forecast error variance matrices
`OmegaR`	Forecast error variance decomposition

Ruey S. Tsay

Tsay (2014, Chapter 3)

p1=matrix(c(0.2,-0.6,0.3,1.1),2,2)
theta1=matrix(c(-0.5,0,0,-0.6),2,2)
Sig=matrix(c(3,1,1,1),2,2)
m1=FEVdec(p1,theta1,Sig)
names(m1)

All-Purpose Toolkit for Analyzing Multivariate Time Series (MTS) and Estimating Multivariate Volatility Models

v1.0

Artistic License 2.0

Authors

Ruey S. Tsay and David Wood

Initial release

2018-10-8