MTS: PIwgt – R documentation

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PIwgt

Pi Weight Matrices

Compute the Pi-weight matrices of a VARMA model

PIwgt(Phi = NULL, Theta = NULL, lag = 12, plot = TRUE)

`Phi`	A k-by-kp matrix of VAR coefficients in the form [Phi1, Phi2, Phi3, ..., Phip]
`Theta`	A k-by-kq matrix of VMA coefficients in the form [Theta1, Theta2, ..., Thetaq]
`lag`	The number of Pi-weight matrices to be computed.
`plot`	A logical switch to plot the Pi-weight matrices

The Pi-weight matrices for a VARMA model is Pi(B) = inverse(Theta(B)) times Phi(B).

pi.weight

The matrix of Pi-weight coefficient

Ruey S. Tsay

Tsay (2014, Chapters 2 and 3). Multivariate Time Series Analysis with R and Financial Applications. John Wiley. Hoboken, NJ.

Phi1=matrix(0,2,2); Phi2=matrix(c(0.2,-0.6,0.3,1.1),2,2)
Theta1=diag(c(-0.5,-0.4))
Phi=cbind(Phi1,Phi2)
m1=PIwgt(Phi=Phi,Theta=Theta1)
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