PIwgt: Pi Weight Matrices

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

Pi Weight Matrices

Description

Compute the Pi-weight matrices of a VARMA model

Usage

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

Arguments

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

Details

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

Value

pi.weight

The matrix of Pi-weight coefficient

Author(s)

Ruey S. Tsay

References

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

See Also

PSIwgt

Examples

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)

MTS documentation built on April 11, 2022, 5:07 p.m.