The Impulse Response Function in the Infinite MA or VMA Representation
The impulse coefficients are computed.
ImpulseVMA(phi=NULL,theta=NULL,trunc.lag=NULL)
phi |
a numeric or an array of |
theta |
a numeric or an array of |
trunc.lag |
truncation lag is used to truncate the infinite |
The impulse response coefficients of order trunc.lag+1 obtained by
converting the ARMA(p,q) or VARMA(p,q)
process to infinite MA or VMA process, respectively.
Esam Mahdi and A.I. McLeod.
Lutkepohl, H. (2005). "New introduction to multiple time series analysis". Springer-Verlag, New York.
Reinsel, G. C. (1997). "Elements of Multivariate Time Series Analysis". Springer-Verlag, 2nd edition.
##################################################################### ### Impulse response coefficients from AR(1,1) to infinite MA process. ### The infinite process is truncated at lag 20 ### k <- 1 trunc.lag <- 20 phi <- 0.7 theta <- array(-0.9,dim=c(k,k,1)) ImpulseVMA(phi,theta,trunc.lag) ##################################################################### ### Impulse response coefficients from VAR(2) to infinite VMA process ### The infinite process is truncated at default lag value = p+q ### k <- 2 phi <- array(c(0.5,0.4,0.1,0.5,0,0.3,0,0),dim=c(k,k,2)) theta <- NULL ImpulseVMA(phi,theta) ##################################################################### ### Impulse response coefficients from VARMA(2,1) to infinite VMA process ### The infinite process is truncated at lag 50 ### k <- 2 phi <- array(c(0.5,0.4,0.1,0.5,0,0.25,0,0),dim=c(k,k,2)) theta <- array(c(0.6,0,0.2,0.3),dim=c(k,k,1)) ImpulseVMA(phi,theta,trunc.lag=50)
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